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@ -22,15 +22,8 @@ AllowShortIfStatementsOnASingleLine: Never
AllowShortLambdasOnASingleLine: Inline
AllowShortLoopsOnASingleLine: false
AlwaysBreakBeforeMultilineStrings: true
# Treat CUDA keywords/attributes as "attribute macros" and avoid breaking lines inside them
AttributeMacros:
- __host__
- __device__
- __global__
- __forceinline__
- __launch_bounds__
BinPackArguments: true
BinPackParameters: false # OnePerLine
BinPackParameters: true # OnePerLine
BitFieldColonSpacing: Both
BreakBeforeBraces: Custom # Attach
BraceWrapping:
@ -77,17 +70,14 @@ ExperimentalAutoDetectBinPacking: false
FixNamespaceComments: true
IncludeBlocks: Regroup
IncludeCategories:
- Regex: '".*"'
- Regex: '^<.*\.h>'
Priority: 1
SortPriority: 0
- Regex: '^<.*\.h>'
- Regex: '^<.*'
Priority: 2
SortPriority: 0
- Regex: '^<.*'
Priority: 3
SortPriority: 0
- Regex: '.*'
Priority: 4
Priority: 3
SortPriority: 0
IncludeIsMainRegex: '([-_](test|unittest))?$'
IncludeIsMainSourceRegex: ''

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@ -17,7 +17,6 @@ Checks: >
clang-analyzer-*,
-clang-analyzer-security.insecureAPI.DeprecatedOrUnsafeBufferHandling,
performance-*,
-performance-enum-size,
portability-*,
-portability-simd-intrinsics,
misc-*,

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@ -1,130 +0,0 @@
# ==============================================================================
# ARGUMENTS
# ==============================================================================
# Define the CANN base image for easier version updates later
ARG CHIP_TYPE=910b
ARG CANN_BASE_IMAGE=quay.io/ascend/cann:8.3.rc2-${CHIP_TYPE}-openeuler24.03-py3.11
# ==============================================================================
# BUILD STAGE
# Compile all binary files and libraries
# ==============================================================================
FROM ${CANN_BASE_IMAGE} AS build
# -- Install build dependencies --
RUN yum install -y gcc g++ cmake make git openssl-devel python3 python3-pip && \
yum clean all && \
rm -rf /var/cache/yum
# -- Set the working directory --
WORKDIR /app
# -- Copy project files --
COPY . .
# -- Set CANN environment variables (required for compilation) --
# Using ENV instead of `source` allows environment variables to persist across the entire image layer
ENV ASCEND_TOOLKIT_HOME=/usr/local/Ascend/ascend-toolkit/latest
ENV LD_LIBRARY_PATH=${ASCEND_TOOLKIT_HOME}/lib64:${LD_LIBRARY_PATH}
ENV PATH=${ASCEND_TOOLKIT_HOME}/bin:${PATH}
ENV ASCEND_OPP_PATH=${ASCEND_TOOLKIT_HOME}/opp
ENV LD_LIBRARY_PATH=${ASCEND_TOOLKIT_HOME}/runtime/lib64/stub:$LD_LIBRARY_PATH
# ... You can add other environment variables from the original file as needed ...
# For brevity, only core variables are listed here. You can paste the original ENV list here.
# -- Build llama.cpp --
# Use the passed CHIP_TYPE argument and add general build options
ARG CHIP_TYPE
RUN source /usr/local/Ascend/ascend-toolkit/set_env.sh --force \
&& \
cmake -B build \
-DGGML_CANN=ON \
-DCMAKE_BUILD_TYPE=Release \
-DSOC_TYPE=ascend${CHIP_TYPE} \
-DUSE_ACL_GRAPH=ON \
. && \
cmake --build build --config Release -j$(nproc)
# -- Organize build artifacts for copying in later stages --
# Create a lib directory to store all .so files
RUN mkdir -p /app/lib && \
find build -name "*.so*" -exec cp -P {} /app/lib \;
# Create a full directory to store all executables and Python scripts
RUN mkdir -p /app/full && \
cp build/bin/* /app/full/ && \
cp *.py /app/full/ && \
cp -r gguf-py /app/full/ && \
cp -r requirements /app/full/ && \
cp requirements.txt /app/full/
# If you have a tools.sh script, make sure it is copied here
# cp .devops/tools.sh /app/full/tools.sh
# ==============================================================================
# BASE STAGE
# Create a minimal base image with CANN runtime and common libraries
# ==============================================================================
FROM ${CANN_BASE_IMAGE} AS base
# -- Install runtime dependencies --
RUN yum install -y libgomp curl && \
yum clean all && \
rm -rf /var/cache/yum
# -- Set CANN environment variables (required for runtime) --
ENV ASCEND_TOOLKIT_HOME=/usr/local/Ascend/ascend-toolkit/latest
ENV LD_LIBRARY_PATH=/app:${ASCEND_TOOLKIT_HOME}/lib64:${LD_LIBRARY_PATH}
ENV PATH=${ASCEND_TOOLKIT_HOME}/bin:${PATH}
ENV ASCEND_OPP_PATH=${ASCEND_TOOLKIT_HOME}/opp
# ... You can add other environment variables from the original file as needed ...
WORKDIR /app
# Copy compiled .so files from the build stage
COPY --from=build /app/lib/ /app
# ==============================================================================
# FINAL STAGES (TARGETS)
# ==============================================================================
### Target: full
# Complete image with all tools, Python bindings, and dependencies
# ==============================================================================
FROM base AS full
COPY --from=build /app/full /app
# Install Python dependencies
RUN yum install -y git python3 python3-pip && \
pip3 install --no-cache-dir --upgrade pip setuptools wheel && \
pip3 install --no-cache-dir -r requirements.txt && \
yum clean all && \
rm -rf /var/cache/yum
# You need to provide a tools.sh script as the entrypoint
ENTRYPOINT ["/app/tools.sh"]
# If there is no tools.sh, you can set the default to start the server
# ENTRYPOINT ["/app/llama-server"]
### Target: light
# Lightweight image containing only llama-cli and llama-completion
# ==============================================================================
FROM base AS light
COPY --from=build /app/full/llama-cli /app/full/llama-completion /app
ENTRYPOINT [ "/app/llama-cli" ]
### Target: server
# Dedicated server image containing only llama-server
# ==============================================================================
FROM base AS server
ENV LLAMA_ARG_HOST=0.0.0.0
COPY --from=build /app/full/llama-server /app
HEALTHCHECK --interval=5m CMD [ "curl", "-f", "http://localhost:8080/health" ]
ENTRYPOINT [ "/app/llama-server" ]

22
.devops/cloud-v-pipeline Normal file
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@ -0,0 +1,22 @@
node('x86_runner1'){ // Running on x86 runner containing latest vector qemu, latest vector gcc and all the necessary libraries
stage('Cleanup'){
cleanWs() // Cleaning previous CI build in workspace
}
stage('checkout repo'){
retry(5){ // Retry if the cloning fails due to some reason
checkout scm // Clone the repo on Runner
}
}
stage('Compiling llama.cpp'){
sh'''#!/bin/bash
make RISCV=1 RISCV_CROSS_COMPILE=1 # Compiling llama for RISC-V
'''
}
stage('Running llama.cpp'){
sh'''#!/bin/bash
module load gnu-bin2/0.1 # loading latest versions of vector qemu and vector gcc
qemu-riscv64 -L /softwares/gnu-bin2/sysroot -cpu rv64,v=true,vlen=256,elen=64,vext_spec=v1.0 ./llama-cli -m /home/alitariq/codellama-7b.Q4_K_M.gguf -p "Anything" -n 9 > llama_log.txt # Running llama.cpp on vector qemu-riscv64
cat llama_log.txt # Printing results
'''
}
}

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@ -4,15 +4,19 @@ FROM ubuntu:$UBUNTU_VERSION AS build
ARG TARGETARCH
ARG GGML_CPU_ARM_ARCH=armv8-a
RUN apt-get update && \
apt-get install -y build-essential git cmake libssl-dev
apt-get install -y build-essential git cmake libcurl4-openssl-dev
WORKDIR /app
COPY . .
RUN if [ "$TARGETARCH" = "amd64" ] || [ "$TARGETARCH" = "arm64" ]; then \
cmake -S . -B build -DCMAKE_BUILD_TYPE=Release -DGGML_NATIVE=OFF -DLLAMA_BUILD_TESTS=OFF -DGGML_BACKEND_DL=ON -DGGML_CPU_ALL_VARIANTS=ON; \
RUN if [ "$TARGETARCH" = "amd64" ]; then \
cmake -S . -B build -DCMAKE_BUILD_TYPE=Release -DGGML_NATIVE=OFF -DGGML_BACKEND_DL=ON -DGGML_CPU_ALL_VARIANTS=ON; \
elif [ "$TARGETARCH" = "arm64" ]; then \
cmake -S . -B build -DCMAKE_BUILD_TYPE=Release -DGGML_NATIVE=OFF -DGGML_CPU_ARM_ARCH=${GGML_CPU_ARM_ARCH}; \
else \
echo "Unsupported architecture"; \
exit 1; \
@ -20,7 +24,7 @@ RUN if [ "$TARGETARCH" = "amd64" ] || [ "$TARGETARCH" = "arm64" ]; then \
cmake --build build -j $(nproc)
RUN mkdir -p /app/lib && \
find build -name "*.so*" -exec cp -P {} /app/lib \;
find build -name "*.so" -exec cp {} /app/lib \;
RUN mkdir -p /app/full \
&& cp build/bin/* /app/full \
@ -68,7 +72,7 @@ ENTRYPOINT ["/app/tools.sh"]
### Light, CLI only
FROM base AS light
COPY --from=build /app/full/llama-cli /app/full/llama-completion /app
COPY --from=build /app/full/llama-cli /app
WORKDIR /app

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@ -1,95 +0,0 @@
ARG UBUNTU_VERSION=24.04
# This needs to generally match the container host's environment.
ARG CUDA_VERSION=13.1.0
# Target the CUDA build image
ARG BASE_CUDA_DEV_CONTAINER=nvidia/cuda:${CUDA_VERSION}-devel-ubuntu${UBUNTU_VERSION}
ARG BASE_CUDA_RUN_CONTAINER=nvidia/cuda:${CUDA_VERSION}-runtime-ubuntu${UBUNTU_VERSION}
FROM ${BASE_CUDA_DEV_CONTAINER} AS build
# CUDA architecture to build for (defaults to all supported archs)
ARG CUDA_DOCKER_ARCH=default
RUN apt-get update && \
apt-get install -y build-essential cmake python3 python3-pip git libssl-dev libgomp1
WORKDIR /app
COPY . .
RUN if [ "${CUDA_DOCKER_ARCH}" != "default" ]; then \
export CMAKE_ARGS="-DCMAKE_CUDA_ARCHITECTURES=${CUDA_DOCKER_ARCH}"; \
fi && \
cmake -B build -DGGML_NATIVE=OFF -DGGML_CUDA=ON -DGGML_BACKEND_DL=ON -DGGML_CPU_ALL_VARIANTS=ON -DLLAMA_BUILD_TESTS=OFF ${CMAKE_ARGS} -DCMAKE_EXE_LINKER_FLAGS=-Wl,--allow-shlib-undefined . && \
cmake --build build --config Release -j$(nproc)
RUN mkdir -p /app/lib && \
find build -name "*.so*" -exec cp -P {} /app/lib \;
RUN mkdir -p /app/full \
&& cp build/bin/* /app/full \
&& cp *.py /app/full \
&& cp -r gguf-py /app/full \
&& cp -r requirements /app/full \
&& cp requirements.txt /app/full \
&& cp .devops/tools.sh /app/full/tools.sh
## Base image
FROM ${BASE_CUDA_RUN_CONTAINER} AS base
RUN apt-get update \
&& apt-get install -y libgomp1 curl\
&& apt autoremove -y \
&& apt clean -y \
&& rm -rf /tmp/* /var/tmp/* \
&& find /var/cache/apt/archives /var/lib/apt/lists -not -name lock -type f -delete \
&& find /var/cache -type f -delete
COPY --from=build /app/lib/ /app
### Full
FROM base AS full
COPY --from=build /app/full /app
WORKDIR /app
RUN apt-get update \
&& apt-get install -y \
git \
python3 \
python3-pip \
python3-wheel \
&& pip install --break-system-packages --upgrade setuptools \
&& pip install --break-system-packages -r requirements.txt \
&& apt autoremove -y \
&& apt clean -y \
&& rm -rf /tmp/* /var/tmp/* \
&& find /var/cache/apt/archives /var/lib/apt/lists -not -name lock -type f -delete \
&& find /var/cache -type f -delete
ENTRYPOINT ["/app/tools.sh"]
### Light, CLI only
FROM base AS light
COPY --from=build /app/full/llama-cli /app/full/llama-completion /app
WORKDIR /app
ENTRYPOINT [ "/app/llama-cli" ]
### Server, Server only
FROM base AS server
ENV LLAMA_ARG_HOST=0.0.0.0
COPY --from=build /app/full/llama-server /app
WORKDIR /app
HEALTHCHECK CMD [ "curl", "-f", "http://localhost:8080/health" ]
ENTRYPOINT [ "/app/llama-server" ]

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@ -12,7 +12,7 @@ FROM ${BASE_CUDA_DEV_CONTAINER} AS build
ARG CUDA_DOCKER_ARCH=default
RUN apt-get update && \
apt-get install -y build-essential cmake python3 python3-pip git libssl-dev libgomp1
apt-get install -y build-essential cmake python3 python3-pip git libcurl4-openssl-dev libgomp1
WORKDIR /app
@ -21,11 +21,11 @@ COPY . .
RUN if [ "${CUDA_DOCKER_ARCH}" != "default" ]; then \
export CMAKE_ARGS="-DCMAKE_CUDA_ARCHITECTURES=${CUDA_DOCKER_ARCH}"; \
fi && \
cmake -B build -DGGML_NATIVE=OFF -DGGML_CUDA=ON -DGGML_BACKEND_DL=ON -DGGML_CPU_ALL_VARIANTS=ON -DLLAMA_BUILD_TESTS=OFF ${CMAKE_ARGS} -DCMAKE_EXE_LINKER_FLAGS=-Wl,--allow-shlib-undefined . && \
cmake -B build -DGGML_NATIVE=OFF -DGGML_CUDA=ON -DLLAMA_CURL=ON -DGGML_BACKEND_DL=ON -DGGML_CPU_ALL_VARIANTS=ON ${CMAKE_ARGS} -DCMAKE_EXE_LINKER_FLAGS=-Wl,--allow-shlib-undefined . && \
cmake --build build --config Release -j$(nproc)
RUN mkdir -p /app/lib && \
find build -name "*.so*" -exec cp -P {} /app/lib \;
find build -name "*.so" -exec cp {} /app/lib \;
RUN mkdir -p /app/full \
&& cp build/bin/* /app/full \
@ -61,7 +61,7 @@ RUN apt-get update \
python3 \
python3-pip \
&& pip install --upgrade pip setuptools wheel \
&& pip install --break-system-packages -r requirements.txt \
&& pip install -r requirements.txt \
&& apt autoremove -y \
&& apt clean -y \
&& rm -rf /tmp/* /var/tmp/* \
@ -74,7 +74,7 @@ ENTRYPOINT ["/app/tools.sh"]
### Light, CLI only
FROM base AS light
COPY --from=build /app/full/llama-cli /app/full/llama-completion /app
COPY --from=build /app/full/llama-cli /app
WORKDIR /app

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@ -1,12 +1,12 @@
ARG ONEAPI_VERSION=2025.2.2-0-devel-ubuntu24.04
ARG ONEAPI_VERSION=2025.0.0-0-devel-ubuntu22.04
## Build Image
FROM intel/deep-learning-essentials:$ONEAPI_VERSION AS build
FROM intel/oneapi-basekit:$ONEAPI_VERSION AS build
ARG GGML_SYCL_F16=OFF
RUN apt-get update && \
apt-get install -y git libssl-dev
apt-get install -y git libcurl4-openssl-dev
WORKDIR /app
@ -17,11 +17,11 @@ RUN if [ "${GGML_SYCL_F16}" = "ON" ]; then \
&& export OPT_SYCL_F16="-DGGML_SYCL_F16=ON"; \
fi && \
echo "Building with dynamic libs" && \
cmake -B build -DGGML_NATIVE=OFF -DGGML_SYCL=ON -DCMAKE_C_COMPILER=icx -DCMAKE_CXX_COMPILER=icpx -DGGML_BACKEND_DL=ON -DGGML_CPU_ALL_VARIANTS=ON -DLLAMA_BUILD_TESTS=OFF ${OPT_SYCL_F16} && \
cmake -B build -DGGML_NATIVE=OFF -DGGML_SYCL=ON -DCMAKE_C_COMPILER=icx -DCMAKE_CXX_COMPILER=icpx -DLLAMA_CURL=ON -DGGML_BACKEND_DL=ON -DGGML_CPU_ALL_VARIANTS=ON ${OPT_SYCL_F16} && \
cmake --build build --config Release -j$(nproc)
RUN mkdir -p /app/lib && \
find build -name "*.so*" -exec cp -P {} /app/lib \;
find build -name "*.so" -exec cp {} /app/lib \;
RUN mkdir -p /app/full \
&& cp build/bin/* /app/full \
@ -31,7 +31,7 @@ RUN mkdir -p /app/full \
&& cp requirements.txt /app/full \
&& cp .devops/tools.sh /app/full/tools.sh
FROM intel/deep-learning-essentials:$ONEAPI_VERSION AS base
FROM intel/oneapi-basekit:$ONEAPI_VERSION AS base
RUN apt-get update \
&& apt-get install -y libgomp1 curl\
@ -49,23 +49,19 @@ COPY --from=build /app/full /app
WORKDIR /app
RUN apt-get update && \
apt-get install -y \
git \
python3 \
python3-pip \
python3-venv && \
python3 -m venv /opt/venv && \
. /opt/venv/bin/activate && \
pip install --upgrade pip setuptools wheel && \
pip install -r requirements.txt && \
apt autoremove -y && \
apt clean -y && \
rm -rf /tmp/* /var/tmp/* && \
find /var/cache/apt/archives /var/lib/apt/lists -not -name lock -type f -delete && \
find /var/cache -type f -delete
RUN apt-get update \
&& apt-get install -y \
git \
python3 \
python3-pip \
&& pip install --upgrade pip setuptools wheel \
&& pip install -r requirements.txt \
&& apt autoremove -y \
&& apt clean -y \
&& rm -rf /tmp/* /var/tmp/* \
&& find /var/cache/apt/archives /var/lib/apt/lists -not -name lock -type f -delete \
&& find /var/cache -type f -delete
ENV PATH="/opt/venv/bin:$PATH"
ENTRYPOINT ["/app/tools.sh"]
@ -73,7 +69,7 @@ ENTRYPOINT ["/app/tools.sh"]
FROM base AS light
COPY --from=build /app/lib/ /app
COPY --from=build /app/full/llama-cli /app/full/llama-completion /app
COPY --from=build /app/full/llama-cli /app
WORKDIR /app

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@ -6,7 +6,7 @@ WORKDIR /app
COPY . .
RUN yum install -y gcc g++ cmake make openssl-devel
RUN yum install -y gcc g++ cmake make libcurl-devel
ENV ASCEND_TOOLKIT_HOME=/usr/local/Ascend/ascend-toolkit/latest
ENV LIBRARY_PATH=${ASCEND_TOOLKIT_HOME}/lib64:$LIBRARY_PATH
ENV LD_LIBRARY_PATH=${ASCEND_TOOLKIT_HOME}/lib64:${ASCEND_TOOLKIT_HOME}/lib64/plugin/opskernel:${ASCEND_TOOLKIT_HOME}/lib64/plugin/nnengine:${ASCEND_TOOLKIT_HOME}/opp/built-in/op_impl/ai_core/tbe/op_tiling:${LD_LIBRARY_PATH}
@ -22,13 +22,12 @@ ENV LD_LIBRARY_PATH=${ASCEND_TOOLKIT_HOME}/runtime/lib64/stub:$LD_LIBRARY_PATH
RUN echo "Building with static libs" && \
source /usr/local/Ascend/ascend-toolkit/set_env.sh --force && \
cmake -B build -DGGML_NATIVE=OFF -DGGML_CANN=ON -DBUILD_SHARED_LIBS=OFF -DLLAMA_BUILD_TESTS=OFF && \
cmake --build build --config Release --target llama-cli && \
cmake --build build --config Release --target llama-completion
cmake -B build -DGGML_NATIVE=OFF -DGGML_CANN=ON -DBUILD_SHARED_LIBS=OFF && \
cmake --build build --config Release --target llama-cli
# TODO: use image with NNRT
FROM ascendai/cann:$ASCEND_VERSION AS runtime
COPY --from=build /app/build/bin/llama-cli /app/build/bin/llama-completion /
COPY --from=build /app/build/bin/llama-cli /llama-cli
ENV LC_ALL=C.utf8

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@ -37,7 +37,6 @@ make -j GGML_CUDA=1
%install
mkdir -p %{buildroot}%{_bindir}/
cp -p llama-cli %{buildroot}%{_bindir}/llama-cuda-cli
cp -p llama-completion %{buildroot}%{_bindir}/llama-cuda-completion
cp -p llama-server %{buildroot}%{_bindir}/llama-cuda-server
cp -p llama-simple %{buildroot}%{_bindir}/llama-cuda-simple
@ -69,7 +68,6 @@ rm -rf %{_builddir}/*
%files
%{_bindir}/llama-cuda-cli
%{_bindir}/llama-cuda-completion
%{_bindir}/llama-cuda-server
%{_bindir}/llama-cuda-simple
/usr/lib/systemd/system/llamacuda.service

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@ -39,7 +39,6 @@ make -j
%install
mkdir -p %{buildroot}%{_bindir}/
cp -p llama-cli %{buildroot}%{_bindir}/llama-cli
cp -p llama-completion %{buildroot}%{_bindir}/llama-completion
cp -p llama-server %{buildroot}%{_bindir}/llama-server
cp -p llama-simple %{buildroot}%{_bindir}/llama-simple
@ -71,7 +70,6 @@ rm -rf %{_builddir}/*
%files
%{_bindir}/llama-cli
%{_bindir}/llama-completion
%{_bindir}/llama-server
%{_bindir}/llama-simple
/usr/lib/systemd/system/llama.service

View File

@ -1,10 +1,10 @@
ARG UBUNTU_VERSION=22.04
# This needs to generally match the container host's environment.
ARG MUSA_VERSION=rc4.3.0
ARG MUSA_VERSION=rc3.1.1
# Target the MUSA build image
ARG BASE_MUSA_DEV_CONTAINER=mthreads/musa:${MUSA_VERSION}-devel-ubuntu${UBUNTU_VERSION}-amd64
ARG BASE_MUSA_DEV_CONTAINER=mthreads/musa:${MUSA_VERSION}-devel-ubuntu${UBUNTU_VERSION}
ARG BASE_MUSA_RUN_CONTAINER=mthreads/musa:${MUSA_VERSION}-runtime-ubuntu${UBUNTU_VERSION}-amd64
ARG BASE_MUSA_RUN_CONTAINER=mthreads/musa:${MUSA_VERSION}-runtime-ubuntu${UBUNTU_VERSION}
FROM ${BASE_MUSA_DEV_CONTAINER} AS build
@ -18,21 +18,28 @@ RUN apt-get update && \
python3 \
python3-pip \
git \
libssl-dev \
libcurl4-openssl-dev \
libgomp1
COPY requirements.txt requirements.txt
COPY requirements requirements
RUN pip install --upgrade pip setuptools wheel \
&& pip install -r requirements.txt
WORKDIR /app
COPY . .
# Use the default MUSA archs if not specified
RUN if [ "${MUSA_DOCKER_ARCH}" != "default" ]; then \
export CMAKE_ARGS="-DMUSA_ARCHITECTURES=${MUSA_DOCKER_ARCH}"; \
fi && \
cmake -B build -DGGML_NATIVE=OFF -DGGML_MUSA=ON -DGGML_BACKEND_DL=ON -DGGML_CPU_ALL_VARIANTS=ON -DLLAMA_BUILD_TESTS=OFF ${CMAKE_ARGS} -DCMAKE_EXE_LINKER_FLAGS=-Wl,--allow-shlib-undefined . && \
cmake -B build -DGGML_NATIVE=OFF -DGGML_MUSA=ON -DLLAMA_CURL=ON -DGGML_BACKEND_DL=ON -DGGML_CPU_ALL_VARIANTS=ON ${CMAKE_ARGS} -DCMAKE_EXE_LINKER_FLAGS=-Wl,--allow-shlib-undefined . && \
cmake --build build --config Release -j$(nproc)
RUN mkdir -p /app/lib && \
find build -name "*.so*" -exec cp -P {} /app/lib \;
find build -name "*.so" -exec cp {} /app/lib \;
RUN mkdir -p /app/full \
&& cp build/bin/* /app/full \
@ -81,7 +88,7 @@ ENTRYPOINT ["/app/tools.sh"]
### Light, CLI only
FROM base AS light
COPY --from=build /app/full/llama-cli /app/full/llama-completion /app
COPY --from=build /app/full/llama-cli /app
WORKDIR /app

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@ -4,7 +4,7 @@
# the module `{ pkgs ... }: { /* config */ }` implicitly uses
# `_module.args.pkgs` (defined in this case by flake-parts).
perSystem =
{ lib, system, ... }:
{ system, ... }:
{
_module.args = {
# Note: bringing up https://zimbatm.com/notes/1000-instances-of-nixpkgs
@ -33,7 +33,7 @@
"CUDA EULA"
"cuDNN EULA"
]
) (p.meta.licenses or (lib.toList p.meta.license));
) (p.meta.licenses or [ p.meta.license ]);
};
# Ensure dependencies use ROCm consistently
pkgsRocm = import inputs.nixpkgs {

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@ -3,7 +3,6 @@
llamaVersion,
numpy,
tqdm,
requests,
sentencepiece,
pyyaml,
poetry-core,
@ -21,7 +20,6 @@ buildPythonPackage {
tqdm
sentencepiece
pyyaml
requests
];
src = lib.cleanSource ../../gguf-py;
pythonImportsCheck = [

View File

@ -32,8 +32,8 @@
useMpi ? false,
useRocm ? config.rocmSupport,
rocmGpuTargets ? builtins.concatStringsSep ";" rocmPackages.clr.gpuTargets,
enableCurl ? true,
useVulkan ? false,
useRpc ? false,
llamaVersion ? "0.0.0", # Arbitrary version, substituted by the flake
# It's necessary to consistently use backendStdenv when building with CUDA support,
@ -47,7 +47,6 @@ let
inherit (lib)
cmakeBool
cmakeFeature
optionalAttrs
optionals
strings
;
@ -128,6 +127,10 @@ effectiveStdenv.mkDerivation (finalAttrs: {
};
postPatch = ''
substituteInPlace ./ggml/src/ggml-metal/ggml-metal.m \
--replace '[bundle pathForResource:@"ggml-metal" ofType:@"metal"];' "@\"$out/bin/ggml-metal.metal\";"
substituteInPlace ./ggml/src/ggml-metal/ggml-metal.m \
--replace '[bundle pathForResource:@"default" ofType:@"metallib"];' "@\"$out/bin/default.metallib\";"
'';
# With PR#6015 https://github.com/ggml-org/llama.cpp/pull/6015,
@ -159,13 +162,15 @@ effectiveStdenv.mkDerivation (finalAttrs: {
++ optionals useMpi [ mpi ]
++ optionals useRocm rocmBuildInputs
++ optionals useBlas [ blas ]
++ optionals useVulkan vulkanBuildInputs;
++ optionals useVulkan vulkanBuildInputs
++ optionals enableCurl [ curl ];
cmakeFlags =
[
(cmakeBool "LLAMA_BUILD_SERVER" true)
(cmakeBool "BUILD_SHARED_LIBS" (!enableStatic))
(cmakeBool "CMAKE_SKIP_BUILD_RPATH" true)
(cmakeBool "LLAMA_CURL" enableCurl)
(cmakeBool "GGML_NATIVE" false)
(cmakeBool "GGML_BLAS" useBlas)
(cmakeBool "GGML_CUDA" useCuda)
@ -173,7 +178,6 @@ effectiveStdenv.mkDerivation (finalAttrs: {
(cmakeBool "GGML_METAL" useMetalKit)
(cmakeBool "GGML_VULKAN" useVulkan)
(cmakeBool "GGML_STATIC" enableStatic)
(cmakeBool "GGML_RPC" useRpc)
]
++ optionals useCuda [
(
@ -193,7 +197,7 @@ effectiveStdenv.mkDerivation (finalAttrs: {
];
# Environment variables needed for ROCm
env = optionalAttrs useRocm {
env = optionals useRocm {
ROCM_PATH = "${rocmPackages.clr}";
HIP_DEVICE_LIB_PATH = "${rocmPackages.rocm-device-libs}/amdgcn/bitcode";
};

View File

@ -7,6 +7,13 @@
let
pythonPackages = python3.pkgs;
buildPythonPackage = pythonPackages.buildPythonPackage;
numpy = pythonPackages.numpy;
tqdm = pythonPackages.tqdm;
sentencepiece = pythonPackages.sentencepiece;
pyyaml = pythonPackages.pyyaml;
poetry-core = pythonPackages.poetry-core;
pytestCheckHook = pythonPackages.pytestCheckHook;
in
# We're using `makeScope` instead of just writing out an attrset
@ -16,18 +23,17 @@ in
lib.makeScope newScope (self: {
inherit llamaVersion;
gguf-py = self.callPackage ./package-gguf-py.nix {
inherit (pythonPackages)
inherit
buildPythonPackage
numpy
tqdm
sentencepiece
poetry-core
pyyaml
pytestCheckHook
requests
buildPythonPackage
poetry-core
;
};
python-scripts = self.callPackage ./python-scripts.nix { inherit (pythonPackages) buildPythonPackage poetry-core; };
python-scripts = self.callPackage ./python-scripts.nix { inherit buildPythonPackage poetry-core; };
llama-cpp = self.callPackage ./package.nix { };
docker = self.callPackage ./docker.nix { };
docker-min = self.callPackage ./docker.nix { interactive = false; };

View File

@ -1,10 +1,10 @@
ARG UBUNTU_VERSION=24.04
# This needs to generally match the container host's environment.
ARG ROCM_VERSION=7.0
ARG AMDGPU_VERSION=7.0
ARG ROCM_VERSION=6.3
ARG AMDGPU_VERSION=6.3
# Target the ROCm build image
# Target the CUDA build image
ARG BASE_ROCM_DEV_CONTAINER=rocm/dev-ubuntu-${UBUNTU_VERSION}:${ROCM_VERSION}-complete
### Build image
@ -13,21 +13,25 @@ FROM ${BASE_ROCM_DEV_CONTAINER} AS build
# Unless otherwise specified, we make a fat build.
# List from https://github.com/ggml-org/llama.cpp/pull/1087#issuecomment-1682807878
# This is mostly tied to rocBLAS supported archs.
# gfx803, gfx900, gfx906, gfx1032, gfx1101, gfx1102,not officialy supported
# check https://rocm.docs.amd.com/projects/install-on-linux/en/docs-6.4.1/reference/system-requirements.html
# gfx803, gfx900, gfx1032, gfx1101, gfx1102,not officialy supported
# gfx906 is deprecated
#check https://rocm.docs.amd.com/projects/install-on-linux/en/docs-6.2.4/reference/system-requirements.html
ARG ROCM_DOCKER_ARCH='gfx803;gfx900;gfx906;gfx908;gfx90a;gfx942;gfx1010;gfx1030;gfx1032;gfx1100;gfx1101;gfx1102;gfx1200;gfx1201;gfx1151'
#ARG ROCM_DOCKER_ARCH='gfx1151'
ARG ROCM_DOCKER_ARCH='gfx803,gfx900,gfx906,gfx908,gfx90a,gfx942,gfx1010,gfx1030,gfx1032,gfx1100,gfx1101,gfx1102'
#ARG ROCM_DOCKER_ARCH=gfx1100
# Set ROCm architectures
# Set nvcc architectured
ENV AMDGPU_TARGETS=${ROCM_DOCKER_ARCH}
# Enable ROCm
# ENV CC=/opt/rocm/llvm/bin/clang
# ENV CXX=/opt/rocm/llvm/bin/clang++
RUN apt-get update \
&& apt-get install -y \
build-essential \
cmake \
git \
libssl-dev \
libcurl4-openssl-dev \
curl \
libgomp1
@ -36,16 +40,11 @@ WORKDIR /app
COPY . .
RUN HIPCXX="$(hipconfig -l)/clang" HIP_PATH="$(hipconfig -R)" \
cmake -S . -B build \
-DGGML_HIP=ON \
-DGGML_HIP_ROCWMMA_FATTN=ON \
-DAMDGPU_TARGETS="$ROCM_DOCKER_ARCH" \
-DGGML_BACKEND_DL=ON -DGGML_CPU_ALL_VARIANTS=ON \
-DCMAKE_BUILD_TYPE=Release -DLLAMA_BUILD_TESTS=OFF \
cmake -S . -B build -DGGML_HIP=ON -DAMDGPU_TARGETS=$ROCM_DOCKER_ARCH -DGGML_BACKEND_DL=ON -DGGML_CPU_ALL_VARIANTS=ON -DCMAKE_BUILD_TYPE=Release -DLLAMA_CURL=ON \
&& cmake --build build --config Release -j$(nproc)
RUN mkdir -p /app/lib \
&& find build -name "*.so*" -exec cp -P {} /app/lib \;
&& find build -name "*.so" -exec cp {} /app/lib \;
RUN mkdir -p /app/full \
&& cp build/bin/* /app/full \
@ -94,7 +93,7 @@ ENTRYPOINT ["/app/tools.sh"]
### Light, CLI only
FROM base AS light
COPY --from=build /app/full/llama-cli /app/full/llama-completion /app
COPY --from=build /app/full/llama-cli /app
WORKDIR /app

View File

@ -1,126 +0,0 @@
ARG GCC_VERSION=15.2.0
ARG UBUNTU_VERSION=24.04
### Build Llama.cpp stage
FROM gcc:${GCC_VERSION} AS build
RUN --mount=type=cache,target=/var/cache/apt,sharing=locked \
--mount=type=cache,target=/var/lib/apt/lists,sharing=locked \
apt update -y && \
apt upgrade -y && \
apt install -y --no-install-recommends \
git cmake ccache ninja-build \
# WARNING: Do not use libopenblas-openmp-dev. libopenblas-dev is faster.
libopenblas-dev libssl-dev && \
rm -rf /var/lib/apt/lists/*
WORKDIR /app
COPY . .
RUN --mount=type=cache,target=/root/.ccache \
--mount=type=cache,target=/app/build \
cmake -S . -B build -G Ninja \
-DCMAKE_BUILD_TYPE=Release \
-DCMAKE_C_COMPILER_LAUNCHER=ccache \
-DCMAKE_CXX_COMPILER_LAUNCHER=ccache \
-DLLAMA_BUILD_TESTS=OFF \
-DGGML_NATIVE=OFF \
-DGGML_BACKEND_DL=ON \
-DGGML_CPU_ALL_VARIANTS=ON \
-DGGML_BLAS=ON \
-DGGML_BLAS_VENDOR=OpenBLAS && \
cmake --build build --config Release -j $(nproc) && \
cmake --install build --prefix /opt/llama.cpp
COPY *.py /opt/llama.cpp/bin
COPY .devops/tools.sh /opt/llama.cpp/bin
COPY gguf-py /opt/llama.cpp/gguf-py
COPY requirements.txt /opt/llama.cpp/gguf-py
COPY requirements /opt/llama.cpp/gguf-py/requirements
### Collect all llama.cpp binaries, libraries and distro libraries
FROM scratch AS collector
# Copy llama.cpp binaries and libraries
COPY --from=build /opt/llama.cpp/bin /llama.cpp/bin
COPY --from=build /opt/llama.cpp/lib /llama.cpp/lib
COPY --from=build /opt/llama.cpp/gguf-py /llama.cpp/gguf-py
### Base image
FROM ubuntu:${UBUNTU_VERSION} AS base
RUN --mount=type=cache,target=/var/cache/apt,sharing=locked \
--mount=type=cache,target=/var/lib/apt/lists,sharing=locked \
apt update -y && \
apt install -y --no-install-recommends \
# WARNING: Do not use libopenblas-openmp-dev. libopenblas-dev is faster.
# See: https://github.com/ggml-org/llama.cpp/pull/15915#issuecomment-3317166506
curl libgomp1 libopenblas-dev && \
apt autoremove -y && \
apt clean -y && \
rm -rf /tmp/* /var/tmp/* && \
find /var/cache/apt/archives /var/lib/apt/lists -not -name lock -type f -delete && \
find /var/cache -type f -delete
# Copy llama.cpp libraries
COPY --from=collector /llama.cpp/lib /usr/lib/s390x-linux-gnu
### Full
FROM base AS full
ENV PATH="/root/.cargo/bin:${PATH}"
WORKDIR /app
RUN --mount=type=cache,target=/var/cache/apt,sharing=locked \
--mount=type=cache,target=/var/lib/apt/lists,sharing=locked \
apt update -y && \
apt install -y \
git cmake libjpeg-dev \
python3 python3-pip python3-dev && \
apt autoremove -y && \
apt clean -y && \
rm -rf /tmp/* /var/tmp/* && \
find /var/cache/apt/archives /var/lib/apt/lists -not -name lock -type f -delete && \
find /var/cache -type f -delete
RUN curl https://sh.rustup.rs -sSf | bash -s -- -y
COPY --from=collector /llama.cpp/bin /app
COPY --from=collector /llama.cpp/gguf-py /app/gguf-py
RUN pip install --no-cache-dir --break-system-packages \
-r /app/gguf-py/requirements.txt
ENTRYPOINT [ "/app/tools.sh" ]
### CLI Only
FROM base AS light
WORKDIR /llama.cpp/bin
# Copy llama.cpp binaries and libraries
COPY --from=collector /llama.cpp/bin/*.so /llama.cpp/bin
COPY --from=collector /llama.cpp/bin/llama-cli /llama.cpp/bin/llama-completion /llama.cpp/bin
ENTRYPOINT [ "/llama.cpp/bin/llama-cli" ]
### Server
FROM base AS server
ENV LLAMA_ARG_HOST=0.0.0.0
WORKDIR /llama.cpp/bin
# Copy llama.cpp binaries and libraries
COPY --from=collector /llama.cpp/bin/*.so /llama.cpp/bin
COPY --from=collector /llama.cpp/bin/llama-server /llama.cpp/bin
EXPOSE 8080
ENTRYPOINT [ "/llama.cpp/bin/llama-server" ]

View File

@ -1,4 +1,4 @@
#!/usr/bin/env bash
#!/bin/bash
set -e
# Read the first argument into a variable
@ -13,8 +13,6 @@ elif [[ "$arg1" == '--quantize' || "$arg1" == '-q' ]]; then
exec ./llama-quantize "$@"
elif [[ "$arg1" == '--run' || "$arg1" == '-r' ]]; then
exec ./llama-cli "$@"
elif [[ "$arg1" == '--run-legacy' || "$arg1" == '-l' ]]; then
exec ./llama-completion "$@"
elif [[ "$arg1" == '--bench' || "$arg1" == '-b' ]]; then
exec ./llama-bench "$@"
elif [[ "$arg1" == '--perplexity' || "$arg1" == '-p' ]]; then
@ -34,10 +32,8 @@ elif [[ "$arg1" == '--server' || "$arg1" == '-s' ]]; then
else
echo "Unknown command: $arg1"
echo "Available commands: "
echo " --run (-r): Run a model (chat) previously converted into ggml"
echo " ex: -m /models/7B/ggml-model-q4_0.bin"
echo " --run-legacy (-l): Run a model (legacy completion) previously converted into ggml"
echo " ex: -m /models/7B/ggml-model-q4_0.bin -no-cnv -p \"Building a website can be done in 10 simple steps:\" -n 512"
echo " --run (-r): Run a model previously converted into ggml"
echo " ex: -m /models/7B/ggml-model-q4_0.bin -p \"Building a website can be done in 10 simple steps:\" -n 512"
echo " --bench (-b): Benchmark the performance of the inference for various parameters."
echo " ex: -m model.gguf"
echo " --perplexity (-p): Measure the perplexity of a model over a given text."

View File

@ -1,24 +1,26 @@
ARG UBUNTU_VERSION=26.04
ARG UBUNTU_VERSION=24.04
FROM ubuntu:$UBUNTU_VERSION AS build
# Install build tools
RUN apt update && apt install -y git build-essential cmake wget xz-utils
RUN apt update && apt install -y git build-essential cmake wget
# Install SSL and Vulkan SDK dependencies
RUN apt install -y libssl-dev curl \
libxcb-xinput0 libxcb-xinerama0 libxcb-cursor-dev libvulkan-dev glslc
# Install Vulkan SDK and cURL
RUN wget -qO - https://packages.lunarg.com/lunarg-signing-key-pub.asc | apt-key add - && \
wget -qO /etc/apt/sources.list.d/lunarg-vulkan-noble.list https://packages.lunarg.com/vulkan/lunarg-vulkan-noble.list && \
apt update -y && \
apt-get install -y vulkan-sdk libcurl4-openssl-dev curl
# Build it
WORKDIR /app
COPY . .
RUN cmake -B build -DGGML_NATIVE=OFF -DGGML_VULKAN=ON -DLLAMA_BUILD_TESTS=OFF -DGGML_BACKEND_DL=ON -DGGML_CPU_ALL_VARIANTS=ON && \
RUN cmake -B build -DGGML_NATIVE=OFF -DGGML_VULKAN=1 -DLLAMA_CURL=1 -DGGML_BACKEND_DL=ON -DGGML_CPU_ALL_VARIANTS=ON && \
cmake --build build --config Release -j$(nproc)
RUN mkdir -p /app/lib && \
find build -name "*.so*" -exec cp -P {} /app/lib \;
find build -name "*.so" -exec cp {} /app/lib \;
RUN mkdir -p /app/full \
&& cp build/bin/* /app/full \
@ -32,8 +34,7 @@ RUN mkdir -p /app/full \
FROM ubuntu:$UBUNTU_VERSION AS base
RUN apt-get update \
&& apt-get install -y libgomp1 curl libvulkan1 mesa-vulkan-drivers \
libglvnd0 libgl1 libglx0 libegl1 libgles2 \
&& apt-get install -y libgomp1 curl libvulkan-dev \
&& apt autoremove -y \
&& apt clean -y \
&& rm -rf /tmp/* /var/tmp/* \
@ -51,10 +52,8 @@ WORKDIR /app
RUN apt-get update \
&& apt-get install -y \
build-essential \
git \
python3 \
python3-dev \
python3-pip \
python3-wheel \
&& pip install --break-system-packages --upgrade setuptools \
@ -70,7 +69,7 @@ ENTRYPOINT ["/app/tools.sh"]
### Light, CLI only
FROM base AS light
COPY --from=build /app/full/llama-cli /app/full/llama-completion /app
COPY --from=build /app/full/llama-cli /app
WORKDIR /app

View File

@ -21,15 +21,15 @@ indent_style = tab
[prompts/*.txt]
insert_final_newline = unset
[tools/server/public/*]
[examples/server/public/*]
indent_size = 2
[tools/server/public/deps_*]
[examples/server/public/deps_*]
trim_trailing_whitespace = unset
indent_style = unset
indent_size = unset
[tools/server/deps_*]
[examples/server/deps_*]
trim_trailing_whitespace = unset
indent_style = unset
indent_size = unset
@ -37,7 +37,7 @@ indent_size = unset
[examples/llama.swiftui/llama.swiftui.xcodeproj/*]
indent_style = tab
[tools/cvector-generator/*.txt]
[examples/cvector-generator/*.txt]
trim_trailing_whitespace = unset
insert_final_newline = unset
@ -48,23 +48,3 @@ end_of_line = unset
charset = unset
trim_trailing_whitespace = unset
insert_final_newline = unset
[vendor/miniaudio/miniaudio.h]
trim_trailing_whitespace = unset
insert_final_newline = unset
[tools/server/webui/**]
indent_style = unset
indent_size = unset
end_of_line = unset
charset = unset
trim_trailing_whitespace = unset
insert_final_newline = unset
[benches/**]
indent_style = unset
indent_size = unset
end_of_line = unset
charset = unset
trim_trailing_whitespace = unset
insert_final_newline = unset

View File

@ -2,9 +2,8 @@
max-line-length = 125
ignore = E203,E211,E221,E225,E231,E241,E251,E261,E266,E501,E701,E704,W503
exclude =
# Do not traverse examples and tools
# Do not traverse examples
examples,
tools,
# Do not include package initializers
__init__.py,
# No need to traverse our git directory

View File

@ -1 +0,0 @@
{ "contextFileName": "AGENTS.md" }

View File

@ -8,8 +8,7 @@ body:
value: >
Thanks for taking the time to fill out this bug report!
This issue template is intended for bug reports where the compilation of llama.cpp fails.
Before opening an issue, please confirm that the compilation still fails
after recreating the CMake build directory and with `-DGGML_CCACHE=OFF`.
Before opening an issue, please confirm that the compilation still fails with `-DGGML_CCACHE=OFF`.
If the compilation succeeds with ccache disabled you should be able to permanently fix the issue
by clearing `~/.cache/ccache` (on Linux).
- type: textarea
@ -41,7 +40,7 @@ body:
attributes:
label: GGML backends
description: Which GGML backends do you know to be affected?
options: [AMX, BLAS, CPU, CUDA, HIP, Metal, Musa, RPC, SYCL, Vulkan, OpenCL, zDNN]
options: [AMX, BLAS, CPU, CUDA, HIP, Kompute, Metal, Musa, RPC, SYCL, Vulkan]
multiple: true
validations:
required: true

View File

@ -11,7 +11,7 @@ body:
(i.e. the generated text) are incorrect or llama.cpp crashes during model evaluation.
If you encountered the issue while using an external UI (e.g. ollama),
please reproduce your issue using one of the examples/binaries in this repository.
The `llama-completion` binary can be used for simple and reproducible model inference.
The `llama-cli` binary can be used for simple and reproducible model inference.
- type: textarea
id: version
attributes:
@ -42,7 +42,7 @@ body:
attributes:
label: GGML backends
description: Which GGML backends do you know to be affected?
options: [AMX, BLAS, CPU, CUDA, HIP, Metal, Musa, RPC, SYCL, Vulkan, OpenCL, zDNN]
options: [AMX, BLAS, CPU, CUDA, HIP, Kompute, Metal, Musa, RPC, SYCL, Vulkan]
multiple: true
validations:
required: true
@ -74,12 +74,9 @@ body:
Please give us a summary of the problem and tell us how to reproduce it.
If you can narrow down the bug to specific hardware, compile flags, or command line arguments,
that information would be very much appreciated by us.
If possible, please try to reproduce the issue using `llama-completion` with `-fit off`.
If you can only reproduce the issue with `-fit on`, please provide logs both with and without `--verbose`.
placeholder: >
e.g. when I run llama-completion with `-fa on` I get garbled outputs for very long prompts.
With short prompts or `-fa off` it works correctly.
e.g. when I run llama-cli with -ngl 99 I get garbled outputs.
When I use -ngl 0 it works correctly.
Here are the exact commands that I used: ...
validations:
required: true
@ -98,18 +95,7 @@ body:
label: Relevant log output
description: >
Please copy and paste any relevant log output, including the command that you entered and any generated text.
For very long logs (thousands of lines), preferably upload them as files instead.
On Linux you can redirect console output into a file by appending ` > llama.log 2>&1` to your command.
value: |
<details>
<summary>Logs</summary>
<!-- Copy-pasted short logs go into the "console" area here -->
```console
```
</details>
<!-- Long logs that you upload as files go here, outside the "console" area -->
This will be automatically formatted into code, so no need for backticks.
render: shell
validations:
required: true

View File

@ -85,19 +85,7 @@ body:
label: Relevant log output
description: >
If applicable, please copy and paste any relevant log output, including any generated text.
If you are encountering problems specifically with the `llama_params_fit` module, always upload `--verbose` logs as well.
For very long logs (thousands of lines), please upload them as files instead.
On Linux you can redirect console output into a file by appending ` > llama.log 2>&1` to your command.
value: |
<details>
<summary>Logs</summary>
<!-- Copy-pasted short logs go into the "console" area here -->
```console
```
</details>
<!-- Long logs that you upload as files go here, outside the "console" area -->
This will be automatically formatted into code, so no need for backticks.
render: shell
validations:
required: false

View File

@ -1,22 +0,0 @@
name: "Determine tag name"
description: "Determine the tag name to use for a release"
outputs:
name:
description: "The name of the tag"
value: ${{ steps.tag.outputs.name }}
runs:
using: "composite"
steps:
- name: Determine tag name
id: tag
shell: bash
run: |
BUILD_NUMBER="$(git rev-list --count HEAD)"
SHORT_HASH="$(git rev-parse --short=7 HEAD)"
if [[ "${{ env.BRANCH_NAME }}" == "master" ]]; then
echo "name=b${BUILD_NUMBER}" >> $GITHUB_OUTPUT
else
SAFE_NAME=$(echo "${{ env.BRANCH_NAME }}" | tr '/' '-')
echo "name=${SAFE_NAME}-b${BUILD_NUMBER}-${SHORT_HASH}" >> $GITHUB_OUTPUT
fi

View File

@ -1,36 +0,0 @@
name: "Install exe"
description: "Download and install exe"
inputs:
url:
description: "URL of the exe installer"
required: true
args:
description: "Installer arguments"
required: true
timeout:
description: "Timeout (in ms)"
required: false
default: "600000"
runs:
using: "composite"
steps:
- name: Install EXE
shell: pwsh
run: |
$ErrorActionPreference = "Stop"
write-host "Downloading Installer EXE"
Invoke-WebRequest -Uri "${{ inputs.url }}" -OutFile "${env:RUNNER_TEMP}\temp-install.exe"
write-host "Installing"
$proc = Start-Process "${env:RUNNER_TEMP}\temp-install.exe" -ArgumentList '${{ inputs.args }}' -NoNewWindow -PassThru
$completed = $proc.WaitForExit(${{ inputs.timeout }})
if (-not $completed) {
Write-Error "Installer timed out. Killing the process"
$proc.Kill()
exit 1
}
if ($proc.ExitCode -ne 0) {
Write-Error "Installer failed with exit code $($proc.ExitCode)"
exit 1
}
write-host "Completed installation"

View File

@ -1,20 +0,0 @@
name: "Linux - Setup SpacemiT Toolchain"
description: "Setup SpacemiT Toolchain for Linux"
inputs:
path:
description: "Installation path"
required: true
version:
description: "SpacemiT toolchain version"
required: true
runs:
using: "composite"
steps:
- name: Setup SpacemiT Toolchain
id: setup
uses: ./.github/actions/unarchive-tar
with:
url: https://archive.spacemit.com/toolchain/spacemit-toolchain-linux-glibc-x86_64-v${{ inputs.version }}.tar.xz
path: ${{ inputs.path }}
strip: 1

View File

@ -1,20 +0,0 @@
name: "Linux - Setup Vulkan SDK"
description: "Setup Vulkan SDK for Linux"
inputs:
path:
description: "Installation path"
required: true
version:
description: "Vulkan SDK version"
required: true
runs:
using: "composite"
steps:
- name: Setup Vulkan SDK
id: setup
uses: ./.github/actions/unarchive-tar
with:
url: https://sdk.lunarg.com/sdk/download/${{ inputs.version }}/linux/vulkan_sdk.tar.xz
path: ${{ inputs.path }}
strip: 1

View File

@ -1,27 +0,0 @@
name: "Unarchive tar"
description: "Download and unarchive tar into directory"
inputs:
url:
description: "URL of the tar archive"
required: true
path:
description: "Directory to unarchive into"
required: true
type:
description: "Compression type (tar option)"
required: false
default: "J"
strip:
description: "Strip components"
required: false
default: "0"
runs:
using: "composite"
steps:
- name: Unarchive into directory
shell: bash
run: |
mkdir -p ${{ inputs.path }}
cd ${{ inputs.path }}
curl --no-progress-meter ${{ inputs.url }} | tar -${{ inputs.type }}x --strip-components=${{ inputs.strip }}

View File

@ -1,98 +0,0 @@
name: "Windows - Setup CUDA Toolkit"
description: "Setup CUDA Toolkit for Windows"
inputs:
cuda_version:
description: "CUDA toolkit version"
required: true
runs:
using: "composite"
steps:
- name: Install Cuda Toolkit 11.7
if: ${{ inputs.cuda_version == '11.7' }}
shell: pwsh
run: |
mkdir -p "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.7"
choco install unzip -y
curl -O "https://developer.download.nvidia.com/compute/cuda/redist/cuda_cudart/windows-x86_64/cuda_cudart-windows-x86_64-11.7.99-archive.zip"
curl -O "https://developer.download.nvidia.com/compute/cuda/redist/cuda_nvcc/windows-x86_64/cuda_nvcc-windows-x86_64-11.7.99-archive.zip"
curl -O "https://developer.download.nvidia.com/compute/cuda/redist/cuda_nvrtc/windows-x86_64/cuda_nvrtc-windows-x86_64-11.7.99-archive.zip"
curl -O "https://developer.download.nvidia.com/compute/cuda/redist/libcublas/windows-x86_64/libcublas-windows-x86_64-11.7.4.6-archive.zip"
curl -O "https://developer.download.nvidia.com/compute/cuda/redist/cuda_nvtx/windows-x86_64/cuda_nvtx-windows-x86_64-11.7.91-archive.zip"
curl -O "https://developer.download.nvidia.com/compute/cuda/redist/visual_studio_integration/windows-x86_64/visual_studio_integration-windows-x86_64-11.7.91-archive.zip"
curl -O "https://developer.download.nvidia.com/compute/cuda/redist/cuda_nvprof/windows-x86_64/cuda_nvprof-windows-x86_64-11.7.101-archive.zip"
curl -O "https://developer.download.nvidia.com/compute/cuda/redist/cuda_cccl/windows-x86_64/cuda_cccl-windows-x86_64-11.7.91-archive.zip"
unzip '*.zip' -d "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.7"
xcopy "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.7\cuda_cudart-windows-x86_64-11.7.99-archive\*" "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.7" /E /I /H /Y
xcopy "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.7\cuda_nvcc-windows-x86_64-11.7.99-archive\*" "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.7" /E /I /H /Y
xcopy "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.7\cuda_nvrtc-windows-x86_64-11.7.99-archive\*" "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.7" /E /I /H /Y
xcopy "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.7\libcublas-windows-x86_64-11.7.4.6-archive\*" "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.7" /E /I /H /Y
xcopy "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.7\cuda_nvtx-windows-x86_64-11.7.91-archive\*" "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.7" /E /I /H /Y
xcopy "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.7\visual_studio_integration-windows-x86_64-11.7.91-archive\*" "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.7" /E /I /H /Y
xcopy "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.7\cuda_nvprof-windows-x86_64-11.7.101-archive\*" "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.7" /E /I /H /Y
xcopy "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.7\cuda_cccl-windows-x86_64-11.7.91-archive\*" "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.7" /E /I /H /Y
echo "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.7\bin" | Out-File -FilePath $env:GITHUB_PATH -Encoding utf8 -Append
echo "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.7\libnvvp" | Out-File -FilePath $env:GITHUB_PATH -Encoding utf8 -Append
echo "CUDA_PATH=C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.7" | Out-File -FilePath $env:GITHUB_ENV -Append -Encoding utf8
echo "CUDA_PATH_V11_7=C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.7" | Out-File -FilePath $env:GITHUB_ENV -Append -Encoding utf8
- name: Install Cuda Toolkit 12.4
if: ${{ inputs.cuda_version == '12.4' }}
shell: pwsh
run: |
mkdir -p "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v12.4"
choco install unzip -y
curl -O "https://developer.download.nvidia.com/compute/cuda/redist/cuda_cudart/windows-x86_64/cuda_cudart-windows-x86_64-12.4.127-archive.zip"
curl -O "https://developer.download.nvidia.com/compute/cuda/redist/cuda_nvcc/windows-x86_64/cuda_nvcc-windows-x86_64-12.4.131-archive.zip"
curl -O "https://developer.download.nvidia.com/compute/cuda/redist/cuda_nvrtc/windows-x86_64/cuda_nvrtc-windows-x86_64-12.4.127-archive.zip"
curl -O "https://developer.download.nvidia.com/compute/cuda/redist/libcublas/windows-x86_64/libcublas-windows-x86_64-12.4.5.8-archive.zip"
curl -O "https://developer.download.nvidia.com/compute/cuda/redist/cuda_nvtx/windows-x86_64/cuda_nvtx-windows-x86_64-12.4.127-archive.zip"
curl -O "https://developer.download.nvidia.com/compute/cuda/redist/cuda_profiler_api/windows-x86_64/cuda_profiler_api-windows-x86_64-12.4.127-archive.zip"
curl -O "https://developer.download.nvidia.com/compute/cuda/redist/visual_studio_integration/windows-x86_64/visual_studio_integration-windows-x86_64-12.4.127-archive.zip"
curl -O "https://developer.download.nvidia.com/compute/cuda/redist/cuda_nvprof/windows-x86_64/cuda_nvprof-windows-x86_64-12.4.127-archive.zip"
curl -O "https://developer.download.nvidia.com/compute/cuda/redist/cuda_cccl/windows-x86_64/cuda_cccl-windows-x86_64-12.4.127-archive.zip"
unzip '*.zip' -d "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v12.4"
xcopy "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v12.4\cuda_cudart-windows-x86_64-12.4.127-archive\*" "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v12.4" /E /I /H /Y
xcopy "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v12.4\cuda_nvcc-windows-x86_64-12.4.131-archive\*" "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v12.4" /E /I /H /Y
xcopy "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v12.4\cuda_nvrtc-windows-x86_64-12.4.127-archive\*" "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v12.4" /E /I /H /Y
xcopy "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v12.4\libcublas-windows-x86_64-12.4.5.8-archive\*" "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v12.4" /E /I /H /Y
xcopy "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v12.4\cuda_nvtx-windows-x86_64-12.4.127-archive\*" "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v12.4" /E /I /H /Y
xcopy "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v12.4\cuda_profiler_api-windows-x86_64-12.4.127-archive\*" "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v12.4" /E /I /H /Y
xcopy "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v12.4\visual_studio_integration-windows-x86_64-12.4.127-archive\*" "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v12.4" /E /I /H /Y
xcopy "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v12.4\cuda_nvprof-windows-x86_64-12.4.127-archive\*" "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v12.4" /E /I /H /Y
xcopy "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v12.4\cuda_cccl-windows-x86_64-12.4.127-archive\*" "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v12.4" /E /I /H /Y
echo "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v12.4\bin" | Out-File -FilePath $env:GITHUB_PATH -Encoding utf8 -Append
echo "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v12.4\libnvvp" | Out-File -FilePath $env:GITHUB_PATH -Encoding utf8 -Append
echo "CUDA_PATH=C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v12.4" | Out-File -FilePath $env:GITHUB_ENV -Append -Encoding utf8
echo "CUDA_PATH_V12_4=C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v12.4" | Out-File -FilePath $env:GITHUB_ENV -Append -Encoding utf8
- name: Install Cuda Toolkit 13.1
if: ${{ inputs.cuda_version == '13.1' }}
shell: pwsh
run: |
mkdir -p "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v13.1"
choco install unzip -y
curl -O "https://developer.download.nvidia.com/compute/cuda/redist/cuda_crt/windows-x86_64/cuda_crt-windows-x86_64-13.1.80-archive.zip"
curl -O "https://developer.download.nvidia.com/compute/cuda/redist/cuda_cudart/windows-x86_64/cuda_cudart-windows-x86_64-13.1.80-archive.zip"
curl -O "https://developer.download.nvidia.com/compute/cuda/redist/cuda_nvcc/windows-x86_64/cuda_nvcc-windows-x86_64-13.1.80-archive.zip"
curl -O "https://developer.download.nvidia.com/compute/cuda/redist/cuda_nvrtc/windows-x86_64/cuda_nvrtc-windows-x86_64-13.1.80-archive.zip"
curl -O "https://developer.download.nvidia.com/compute/cuda/redist/libcublas/windows-x86_64/libcublas-windows-x86_64-13.2.0.9-archive.zip"
curl -O "https://developer.download.nvidia.com/compute/cuda/redist/libnvvm/windows-x86_64/libnvvm-windows-x86_64-13.1.80-archive.zip"
curl -O "https://developer.download.nvidia.com/compute/cuda/redist/cuda_nvtx/windows-x86_64/cuda_nvtx-windows-x86_64-13.1.68-archive.zip"
curl -O "https://developer.download.nvidia.com/compute/cuda/redist/cuda_profiler_api/windows-x86_64/cuda_profiler_api-windows-x86_64-13.1.80-archive.zip"
curl -O "https://developer.download.nvidia.com/compute/cuda/redist/visual_studio_integration/windows-x86_64/visual_studio_integration-windows-x86_64-13.1.68-archive.zip"
curl -O "https://developer.download.nvidia.com/compute/cuda/redist/cuda_cccl/windows-x86_64/cuda_cccl-windows-x86_64-13.1.78-archive.zip"
unzip '*.zip' -d "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v13.1"
xcopy "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v13.1\cuda_crt-windows-x86_64-13.1.80-archive\*" "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v13.1" /E /I /H /Y
xcopy "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v13.1\cuda_cudart-windows-x86_64-13.1.80-archive\*" "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v13.1" /E /I /H /Y
xcopy "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v13.1\cuda_nvcc-windows-x86_64-13.1.80-archive\*" "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v13.1" /E /I /H /Y
xcopy "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v13.1\cuda_nvrtc-windows-x86_64-13.1.80-archive\*" "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v13.1" /E /I /H /Y
xcopy "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v13.1\libcublas-windows-x86_64-13.2.0.9-archive\*" "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v13.1" /E /I /H /Y
xcopy "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v13.1\libnvvm-windows-x86_64-13.1.80-archive\*" "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v13.1" /E /I /H /Y
xcopy "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v13.1\cuda_nvtx-windows-x86_64-13.1.68-archive\*" "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v13.1" /E /I /H /Y
xcopy "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v13.1\cuda_profiler_api-windows-x86_64-13.1.80-archive\*" "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v13.1" /E /I /H /Y
xcopy "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v13.1\visual_studio_integration-windows-x86_64-13.1.68-archive\*" "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v13.1" /E /I /H /Y
xcopy "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v13.1\cuda_cccl-windows-x86_64-13.1.78-archive\*" "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v13.1" /E /I /H /Y
echo "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v13.1\bin" | Out-File -FilePath $env:GITHUB_PATH -Encoding utf8 -Append
echo "CUDA_PATH=C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v13.1" | Out-File -FilePath $env:GITHUB_ENV -Append -Encoding utf8
echo "CUDA_PATH_V13_1=C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v13.1" | Out-File -FilePath $env:GITHUB_ENV -Append -Encoding utf8

View File

@ -0,0 +1,25 @@
name: 'Windows - Setup CURL'
description: 'Composite action, to be reused in other workflow'
inputs:
curl_version:
description: 'CURL version'
required: false
default: '8.6.0_6'
outputs:
curl_path:
description: "Path to the downloaded libcurl"
value: ${{ steps.get_libcurl.outputs.curl_path }}
runs:
using: "composite"
steps:
- name: libCURL
id: get_libcurl
shell: powershell
env:
CURL_VERSION: ${{ inputs.curl_version }}
run: |
curl.exe -o $env:RUNNER_TEMP/curl.zip -L "https://curl.se/windows/dl-${env:CURL_VERSION}/curl-${env:CURL_VERSION}-win64-mingw.zip"
mkdir $env:RUNNER_TEMP/libcurl
tar.exe -xvf $env:RUNNER_TEMP/curl.zip --strip-components=1 -C $env:RUNNER_TEMP/libcurl
echo "curl_path=$env:RUNNER_TEMP/libcurl" >> $env:GITHUB_OUTPUT

View File

@ -1,15 +0,0 @@
name: "Windows - Setup ROCm"
description: "Setup ROCm for Windows"
inputs:
version:
description: "ROCm version"
required: true
runs:
using: "composite"
steps:
- name: Setup ROCm
uses: ./.github/actions/install-exe
with:
url: https://download.amd.com/developer/eula/rocm-hub/AMD-Software-PRO-Edition-${{ inputs.version }}-WinSvr2022-For-HIP.exe
args: -install

36
.github/labeler.yml vendored
View File

@ -1,4 +1,10 @@
# https://github.com/actions/labeler
Kompute:
- changed-files:
- any-glob-to-any-file:
- ggml/include/ggml-kompute.h
- ggml/src/ggml-kompute/**
- README-kompute.md
Apple Metal:
- changed-files:
- any-glob-to-any-file:
@ -22,11 +28,6 @@ Vulkan:
- any-glob-to-any-file:
- ggml/include/ggml-vulkan.h
- ggml/src/ggml-vulkan/**
IBM zDNN:
- changed-files:
- any-glob-to-any-file:
- ggml/include/ggml-zdnn.h
- ggml/src/ggml-zdnn/**
documentation:
- changed-files:
- any-glob-to-any-file:
@ -44,9 +45,7 @@ build:
- CMakePresets.json
examples:
- changed-files:
- any-glob-to-any-file:
- examples/**
- tools/**
- any-glob-to-any-file: examples/**
devops:
- changed-files:
- any-glob-to-any-file:
@ -71,15 +70,11 @@ android:
server:
- changed-files:
- any-glob-to-any-file:
- tools/server/**
- examples/server/**
ggml:
- changed-files:
- any-glob-to-any-file:
- ggml/**
model:
- changed-files:
- any-glob-to-any-file:
- src/models/**
nix:
- changed-files:
- any-glob-to-any-file:
@ -89,18 +84,3 @@ nix:
embedding:
- changed-files:
- any-glob-to-any-file: examples/embedding/
jinja parser:
- changed-files:
- any-glob-to-any-file:
- common/jinja/**
Ascend NPU:
- changed-files:
- any-glob-to-any-file:
- ggml/include/ggml-cann.h
- ggml/src/ggml-cann/**
- docs/backend/CANN.md
OpenCL:
- changed-files:
- any-glob-to-any-file:
- ggml/include/ggml-opencl.h
- ggml/src/ggml-opencl/**

View File

@ -27,10 +27,10 @@ on:
push:
branches:
- master
paths: ['llama.cpp', 'ggml.c', 'ggml-backend.cpp', 'ggml-quants.c', '**/*.cu', 'tools/server/*.h*', 'tools/server/*.cpp']
paths: ['llama.cpp', 'ggml.c', 'ggml-backend.cpp', 'ggml-quants.c', '**/*.cu', 'examples/server/*.h*', 'examples/server/*.cpp']
pull_request_target:
types: [opened, synchronize, reopened]
paths: ['llama.cpp', 'ggml.c', 'ggml-backend.cpp', 'ggml-quants.c', '**/*.cu', 'tools/server/*.h*', 'tools/server/*.cpp']
paths: ['llama.cpp', 'ggml.c', 'ggml-backend.cpp', 'ggml-quants.c', '**/*.cu', 'examples/server/*.h*', 'examples/server/*.cpp']
schedule:
- cron: '04 2 * * *'
@ -69,7 +69,7 @@ jobs:
- name: Install python env
id: pipenv
run: |
cd tools/server/bench
cd examples/server/bench
python3 -m venv venv
source venv/bin/activate
pip install -r requirements.txt
@ -79,7 +79,7 @@ jobs:
run: |
wget --quiet https://github.com/prometheus/prometheus/releases/download/v2.51.0/prometheus-2.51.0.linux-amd64.tar.gz
tar xzf prometheus*.tar.gz --strip-components=1
./prometheus --config.file=tools/server/bench/prometheus.yml &
./prometheus --config.file=examples/server/bench/prometheus.yml &
while ! nc -z localhost 9090; do
sleep 0.1
done
@ -92,7 +92,7 @@ jobs:
- name: Install k6 and xk6-sse
id: k6_installation
run: |
cd tools/server/bench
cd examples/server/bench
go install go.k6.io/xk6/cmd/xk6@latest
xk6 build master \
--with github.com/phymbert/xk6-sse
@ -116,7 +116,7 @@ jobs:
- name: Download the dataset
id: download_dataset
run: |
cd tools/server/bench
cd examples/server/bench
wget --quiet https://huggingface.co/datasets/anon8231489123/ShareGPT_Vicuna_unfiltered/resolve/main/ShareGPT_V3_unfiltered_cleaned_split.json
- name: Server bench
@ -126,7 +126,7 @@ jobs:
run: |
set -eux
cd tools/server/bench
cd examples/server/bench
source venv/bin/activate
python bench.py \
--runner-label ${{ env.RUNNER_LABEL }} \
@ -157,9 +157,9 @@ jobs:
name: bench-server-${{ github.job }}-${{ env.RUNNER_LABEL }}-${{ matrix.model }}-${{ matrix.ftype }}
compression-level: 9
path: |
tools/server/bench/*.jpg
tools/server/bench/*.json
tools/server/bench/*.log
examples/server/bench/*.jpg
examples/server/bench/*.json
examples/server/bench/*.log
- name: Commit status
uses: Sibz/github-status-action@v1
@ -178,17 +178,17 @@ jobs:
with:
client_id: ${{secrets.IMGUR_CLIENT_ID}}
path: |
tools/server/bench/prompt_tokens_seconds.jpg
tools/server/bench/predicted_tokens_seconds.jpg
tools/server/bench/kv_cache_usage_ratio.jpg
tools/server/bench/requests_processing.jpg
examples/server/bench/prompt_tokens_seconds.jpg
examples/server/bench/predicted_tokens_seconds.jpg
examples/server/bench/kv_cache_usage_ratio.jpg
examples/server/bench/requests_processing.jpg
- name: Extract mermaid
id: set_mermaid
run: |
set -eux
cd tools/server/bench
cd examples/server/bench
PROMPT_TOKENS_SECONDS=$(cat prompt_tokens_seconds.mermaid)
echo "PROMPT_TOKENS_SECONDS<<EOF" >> $GITHUB_ENV
echo "$PROMPT_TOKENS_SECONDS" >> $GITHUB_ENV

View File

@ -1,89 +0,0 @@
name: Build Actions Cache
on:
workflow_dispatch: # allows manual triggering
schedule:
- cron: '0 * * * *'
concurrency:
group: ${{ github.workflow }}-${{ github.head_ref && github.ref || github.run_id }}
cancel-in-progress: true
jobs:
ubuntu-24-vulkan-cache:
runs-on: ubuntu-24.04
steps:
- name: Clone
id: checkout
uses: actions/checkout@v6
- name: Get latest Vulkan SDK version
id: vulkan_sdk_version
run: |
echo "VULKAN_SDK_VERSION=$(curl https://vulkan.lunarg.com/sdk/latest/linux.txt)" >> "$GITHUB_ENV"
- name: Setup Cache
uses: actions/cache@v5
id: cache-sdk
with:
path: ./vulkan_sdk
key: vulkan-sdk-${{ env.VULKAN_SDK_VERSION }}-${{ runner.os }}
- name: Setup Vulkan SDK
if: steps.cache-sdk.outputs.cache-hit != 'true'
uses: ./.github/actions/linux-setup-vulkan
with:
path: ./vulkan_sdk
version: ${{ env.VULKAN_SDK_VERSION }}
ubuntu-24-spacemit-cache:
runs-on: ubuntu-24.04
env:
# Make sure this is in sync with build-linux-cross.yml
SPACEMIT_IME_TOOLCHAIN_VERSION: "1.1.2"
steps:
- name: Clone
id: checkout
uses: actions/checkout@v6
- name: Setup Cache
uses: actions/cache@v5
id: cache-toolchain
with:
path: ./spacemit_toolchain
key: spacemit-ime-toolchain-v${{ env.SPACEMIT_IME_TOOLCHAIN_VERSION }}-${{ runner.os }}
- name: Setup SpacemiT Toolchain
if: steps.cache-toolchain.outputs.cache-hit != 'true'
uses: ./.github/actions/linux-setup-spacemit
with:
path: ./spacemit_toolchain
version: ${{ env.SPACEMIT_IME_TOOLCHAIN_VERSION }}
windows-2022-rocm-cache:
runs-on: windows-2022
env:
# Make sure this is in sync with build.yml
HIPSDK_INSTALLER_VERSION: "25.Q3"
steps:
- name: Clone
id: checkout
uses: actions/checkout@v6
- name: Setup Cache
uses: actions/cache@v5
id: cache-rocm
with:
path: C:\Program Files\AMD\ROCm
key: rocm-${{ env.HIPSDK_INSTALLER_VERSION }}-${{ runner.os }}
- name: Setup ROCm
if: steps.cache-rocm.outputs.cache-hit != 'true'
uses: ./.github/actions/windows-setup-rocm
with:
version: ${{ env.HIPSDK_INSTALLER_VERSION }}

View File

@ -1,51 +0,0 @@
name: Build relocatable cmake package
on:
workflow_dispatch:
workflow_call:
jobs:
linux:
runs-on: ubuntu-24.04
steps:
- uses: actions/checkout@v6
with:
fetch-depth: 0
- name: Install dependencies
run: |
sudo apt update
sudo apt install -y build-essential tcl
- name: Build
run: |
PREFIX="$(pwd)"/inst
cmake -S . -B build -DCMAKE_PREFIX_PATH="$PREFIX" \
-DLLAMA_OPENSSL=OFF -DLLAMA_BUILD_TESTS=OFF -DLLAMA_BUILD_TOOLS=OFF \
-DLLAMA_BUILD_EXAMPLES=OFF -DCMAKE_BUILD_TYPE=Release
cmake --build build --config Release
cmake --install build --prefix "$PREFIX" --config Release
export LLAMA_CONFIG="$PREFIX"/lib/cmake/llama/llama-config.cmake
tclsh <<'EOF'
set build(commit) [string trim [exec git rev-parse --short HEAD]]
set build(number) [string trim [exec git rev-list --count HEAD]]
set build(version) "0.0.$build(number)"
set llamaconfig [read [open "$env(LLAMA_CONFIG)" r]]
set checks [list "set\\(LLAMA_VERSION \\s+$build(version)\\)" \
"set\\(LLAMA_BUILD_COMMIT\\s+$build(commit)\\)" \
"set\\(LLAMA_BUILD_NUMBER\\s+$build(number)\\)"]
puts -nonewline "Checking llama-config.cmake version... "
foreach check $checks {
if {![regexp -expanded -- $check $llamaconfig]} {
puts "\"$check\" failed!"
exit 1
}
}
puts "success."
EOF
cd examples/simple-cmake-pkg
cmake -S . -B build -DCMAKE_PREFIX_PATH="$PREFIX"/lib/cmake
cmake --build build

View File

@ -4,295 +4,121 @@ on:
workflow_call:
jobs:
# ubuntu-24-riscv64-cpu-cross:
# runs-on: ubuntu-24.04
# steps:
# - uses: actions/checkout@v6
# - name: Setup Riscv
# run: |
# sudo dpkg --add-architecture riscv64
# # Add arch-specific repositories for non-amd64 architectures
# cat << EOF | sudo tee /etc/apt/sources.list.d/riscv64-ports.list
# deb [arch=riscv64] http://ports.ubuntu.com/ubuntu-ports/ noble main universe
# deb [arch=riscv64] http://ports.ubuntu.com/ubuntu-ports/ noble-updates main universe
# deb [arch=riscv64] http://ports.ubuntu.com/ubuntu-ports/ noble-security main universe
# deb [arch=riscv64] http://ports.ubuntu.com/ubuntu-ports/ noble-backports main universe
# EOF
# sudo apt-get update || true ;# Prevent failure due to missing URLs.
# sudo apt-get install -y --no-install-recommends \
# build-essential \
# gcc-14-riscv64-linux-gnu \
# g++-14-riscv64-linux-gnu
# - name: Build
# run: |
# cmake -B build -DLLAMA_OPENSSL=OFF \
# -DCMAKE_BUILD_TYPE=Release \
# -DGGML_OPENMP=OFF \
# -DLLAMA_BUILD_EXAMPLES=ON \
# -DLLAMA_BUILD_TOOLS=ON \
# -DLLAMA_BUILD_TESTS=OFF \
# -DCMAKE_SYSTEM_NAME=Linux \
# -DCMAKE_SYSTEM_PROCESSOR=riscv64 \
# -DCMAKE_C_COMPILER=riscv64-linux-gnu-gcc-14 \
# -DCMAKE_CXX_COMPILER=riscv64-linux-gnu-g++-14 \
# -DCMAKE_POSITION_INDEPENDENT_CODE=ON \
# -DCMAKE_FIND_ROOT_PATH=/usr/lib/riscv64-linux-gnu \
# -DCMAKE_FIND_ROOT_PATH_MODE_PROGRAM=NEVER \
# -DCMAKE_FIND_ROOT_PATH_MODE_LIBRARY=ONLY \
# -DCMAKE_FIND_ROOT_PATH_MODE_INCLUDE=BOTH
# cmake --build build --config Release -j $(nproc)
# ubuntu-24-riscv64-vulkan-cross:
# runs-on: ubuntu-24.04
# steps:
# - uses: actions/checkout@v6
# - name: Setup Riscv
# run: |
# sudo dpkg --add-architecture riscv64
# # Add arch-specific repositories for non-amd64 architectures
# cat << EOF | sudo tee /etc/apt/sources.list.d/riscv64-ports.list
# deb [arch=riscv64] http://ports.ubuntu.com/ubuntu-ports/ noble main universe
# deb [arch=riscv64] http://ports.ubuntu.com/ubuntu-ports/ noble-updates main universe
# deb [arch=riscv64] http://ports.ubuntu.com/ubuntu-ports/ noble-security main universe
# deb [arch=riscv64] http://ports.ubuntu.com/ubuntu-ports/ noble-backports main universe
# EOF
# sudo apt-get update || true ;# Prevent failure due to missing URLs.
# sudo apt-get install -y --no-install-recommends \
# build-essential \
# glslc \
# gcc-14-riscv64-linux-gnu \
# g++-14-riscv64-linux-gnu \
# libvulkan-dev:riscv64
# - name: Build
# run: |
# cmake -B build -DLLAMA_OPENSSL=OFF \
# -DCMAKE_BUILD_TYPE=Release \
# -DGGML_VULKAN=ON \
# -DGGML_OPENMP=OFF \
# -DLLAMA_BUILD_EXAMPLES=ON \
# -DLLAMA_BUILD_TOOLS=ON \
# -DLLAMA_BUILD_TESTS=OFF \
# -DCMAKE_SYSTEM_NAME=Linux \
# -DCMAKE_SYSTEM_PROCESSOR=riscv64 \
# -DCMAKE_C_COMPILER=riscv64-linux-gnu-gcc-14 \
# -DCMAKE_CXX_COMPILER=riscv64-linux-gnu-g++-14 \
# -DCMAKE_POSITION_INDEPENDENT_CODE=ON \
# -DCMAKE_FIND_ROOT_PATH=/usr/lib/riscv64-linux-gnu \
# -DCMAKE_FIND_ROOT_PATH_MODE_PROGRAM=NEVER \
# -DCMAKE_FIND_ROOT_PATH_MODE_LIBRARY=ONLY \
# -DCMAKE_FIND_ROOT_PATH_MODE_INCLUDE=BOTH
# cmake --build build --config Release -j $(nproc)
# ubuntu-24-arm64-vulkan-cross:
# runs-on: ubuntu-24.04
# steps:
# - uses: actions/checkout@v6
# - name: Setup Arm64
# run: |
# sudo dpkg --add-architecture arm64
# # Add arch-specific repositories for non-amd64 architectures
# cat << EOF | sudo tee /etc/apt/sources.list.d/arm64-ports.list
# deb [arch=arm64] http://ports.ubuntu.com/ubuntu-ports/ noble main universe
# deb [arch=arm64] http://ports.ubuntu.com/ubuntu-ports/ noble-updates main universe
# deb [arch=arm64] http://ports.ubuntu.com/ubuntu-ports/ noble-security main universe
# deb [arch=arm64] http://ports.ubuntu.com/ubuntu-ports/ noble-backports main universe
# EOF
# sudo apt-get update || true ;# Prevent failure due to missing URLs.
# sudo apt-get install -y --no-install-recommends \
# build-essential \
# glslc \
# crossbuild-essential-arm64 \
# libvulkan-dev:arm64
# - name: Build
# run: |
# cmake -B build -DLLAMA_OPENSSL=OFF \
# -DCMAKE_BUILD_TYPE=Release \
# -DGGML_VULKAN=ON \
# -DGGML_OPENMP=OFF \
# -DLLAMA_BUILD_EXAMPLES=ON \
# -DLLAMA_BUILD_TOOLS=ON \
# -DLLAMA_BUILD_TESTS=OFF \
# -DCMAKE_SYSTEM_NAME=Linux \
# -DCMAKE_SYSTEM_PROCESSOR=aarch64 \
# -DCMAKE_C_COMPILER=aarch64-linux-gnu-gcc \
# -DCMAKE_CXX_COMPILER=aarch64-linux-gnu-g++ \
# -DCMAKE_POSITION_INDEPENDENT_CODE=ON \
# -DCMAKE_FIND_ROOT_PATH=/usr/lib/aarch64-linux-gnu \
# -DCMAKE_FIND_ROOT_PATH_MODE_PROGRAM=NEVER \
# -DCMAKE_FIND_ROOT_PATH_MODE_LIBRARY=ONLY \
# -DCMAKE_FIND_ROOT_PATH_MODE_INCLUDE=BOTH
# cmake --build build --config Release -j $(nproc)
debian-13-loongarch64-cpu-cross:
runs-on: ubuntu-24.04
container: debian@sha256:653dfb9f86c3782e8369d5f7d29bb8faba1f4bff9025db46e807fa4c22903671
ubuntu-latest-riscv64-cpu-cross:
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v6
- name: Setup LoongArch
- uses: actions/checkout@v4
- name: Setup Riscv
run: |
rm -f /etc/apt/sources.list.d/*
cat << EOF | tee /etc/apt/sources.list.d/debian-ports.list
deb http://snapshot.debian.org/archive/debian/20250515T202920Z/ trixie main
EOF
( echo 'quiet "true";'; \
echo 'APT::Get::Assume-Yes "true";'; \
echo 'APT::Install-Recommends "false";'; \
echo 'Acquire::Check-Valid-Until "false";'; \
echo 'Acquire::Retries "5";'; \
) > /etc/apt/apt.conf.d/99snapshot-repos
apt-get update
apt-get install -y ca-certificates debian-ports-archive-keyring cmake git zip
dpkg --add-architecture loong64
# Add arch-specific repositories for non-amd64 architectures
cat << EOF | tee /etc/apt/sources.list.d/loong64-ports.list
deb [arch=loong64] http://snapshot.debian.org/archive/debian-ports/20250515T194251Z/ sid main
EOF
apt-get update || true ;# Prevent failure due to missing URLs.
apt-get install -y --no-install-recommends \
sudo dpkg --add-architecture riscv64
sudo sed -i 's|http://azure.archive.ubuntu.com/ubuntu|http://ports.ubuntu.com/ubuntu-ports|g' \
/etc/apt/sources.list /etc/apt/apt-mirrors.txt
sudo apt-get clean
sudo apt-get update
sudo apt-get install -y --no-install-recommends \
build-essential \
gcc-14-loongarch64-linux-gnu \
g++-14-loongarch64-linux-gnu
gcc-14-riscv64-linux-gnu \
g++-14-riscv64-linux-gnu \
libcurl4-openssl-dev:riscv64
- name: Build
run: |
cmake -B build -DLLAMA_OPENSSL=OFF \
-DCMAKE_BUILD_TYPE=Release \
cmake -B build -DCMAKE_BUILD_TYPE=Release \
-DGGML_OPENMP=OFF \
-DLLAMA_BUILD_EXAMPLES=ON \
-DLLAMA_BUILD_TOOLS=ON \
-DLLAMA_BUILD_TESTS=OFF \
-DCMAKE_SYSTEM_NAME=Linux \
-DCMAKE_SYSTEM_PROCESSOR=loongarch64 \
-DCMAKE_C_COMPILER=loongarch64-linux-gnu-gcc-14 \
-DCMAKE_CXX_COMPILER=loongarch64-linux-gnu-g++-14 \
-DCMAKE_SYSTEM_PROCESSOR=riscv64 \
-DCMAKE_C_COMPILER=riscv64-linux-gnu-gcc-14 \
-DCMAKE_CXX_COMPILER=riscv64-linux-gnu-g++-14 \
-DCMAKE_POSITION_INDEPENDENT_CODE=ON \
-DCMAKE_FIND_ROOT_PATH=/usr/lib/loongarch64-linux-gnu \
-DCMAKE_FIND_ROOT_PATH=/usr/lib/riscv64-linux-gnu \
-DCMAKE_FIND_ROOT_PATH_MODE_PROGRAM=NEVER \
-DCMAKE_FIND_ROOT_PATH_MODE_LIBRARY=ONLY \
-DCMAKE_FIND_ROOT_PATH_MODE_INCLUDE=BOTH
cmake --build build --config Release -j $(nproc)
debian-13-loongarch64-vulkan-cross:
runs-on: ubuntu-24.04
container: debian@sha256:653dfb9f86c3782e8369d5f7d29bb8faba1f4bff9025db46e807fa4c22903671
ubuntu-latest-riscv64-vulkan-cross:
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v6
- name: Setup LoongArch
- uses: actions/checkout@v4
with:
fetch-depth: 0
- name: Setup Riscv
run: |
rm -f /etc/apt/sources.list.d/*
cat << EOF | tee /etc/apt/sources.list.d/debian-ports.list
deb http://snapshot.debian.org/archive/debian/20250515T202920Z/ trixie main
EOF
( echo 'quiet "true";'; \
echo 'APT::Get::Assume-Yes "true";'; \
echo 'APT::Install-Recommends "false";'; \
echo 'Acquire::Check-Valid-Until "false";'; \
echo 'Acquire::Retries "5";'; \
) > /etc/apt/apt.conf.d/99snapshot-repos
apt-get update
apt-get install -y ca-certificates debian-ports-archive-keyring cmake git zip
dpkg --add-architecture loong64
# Add arch-specific repositories for non-amd64 architectures
cat << EOF | tee /etc/apt/sources.list.d/loong64-ports.list
deb [arch=loong64] http://snapshot.debian.org/archive/debian-ports/20250515T194251Z/ sid main
EOF
apt-get update || true ;# Prevent failure due to missing URLs.
apt-get install -y --no-install-recommends \
sudo dpkg --add-architecture riscv64
sudo sed -i 's|http://azure.archive.ubuntu.com/ubuntu|http://ports.ubuntu.com/ubuntu-ports|g' \
/etc/apt/sources.list /etc/apt/apt-mirrors.txt
sudo apt-get clean
sudo apt-get update
sudo apt-get install -y --no-install-recommends \
build-essential \
glslc \
gcc-14-loongarch64-linux-gnu \
g++-14-loongarch64-linux-gnu \
libvulkan-dev:loong64
gcc-14-riscv64-linux-gnu \
g++-14-riscv64-linux-gnu \
libvulkan-dev:riscv64 \
libcurl4-openssl-dev:riscv64
- name: Build
run: |
cmake -B build -DLLAMA_OPENSSL=OFF \
-DCMAKE_BUILD_TYPE=Release \
cmake -B build -DCMAKE_BUILD_TYPE=Release \
-DGGML_VULKAN=ON \
-DGGML_OPENMP=OFF \
-DLLAMA_BUILD_EXAMPLES=ON \
-DLLAMA_BUILD_TOOLS=ON \
-DLLAMA_BUILD_TESTS=OFF \
-DCMAKE_SYSTEM_NAME=Linux \
-DCMAKE_SYSTEM_PROCESSOR=loongarch64 \
-DCMAKE_C_COMPILER=loongarch64-linux-gnu-gcc-14 \
-DCMAKE_CXX_COMPILER=loongarch64-linux-gnu-g++-14 \
-DCMAKE_SYSTEM_PROCESSOR=riscv64 \
-DCMAKE_C_COMPILER=riscv64-linux-gnu-gcc-14 \
-DCMAKE_CXX_COMPILER=riscv64-linux-gnu-g++-14 \
-DCMAKE_POSITION_INDEPENDENT_CODE=ON \
-DCMAKE_FIND_ROOT_PATH=/usr/lib/loongarch64-linux-gnu \
-DCMAKE_FIND_ROOT_PATH=/usr/lib/riscv64-linux-gnu \
-DCMAKE_FIND_ROOT_PATH_MODE_PROGRAM=NEVER \
-DCMAKE_FIND_ROOT_PATH_MODE_LIBRARY=ONLY \
-DCMAKE_FIND_ROOT_PATH_MODE_INCLUDE=BOTH
cmake --build build --config Release -j $(nproc)
ubuntu-24-riscv64-cpu-spacemit-ime-cross:
runs-on: ubuntu-24.04
env:
# Make sure this is in sync with build-cache.yml
SPACEMIT_IME_TOOLCHAIN_VERSION: "1.1.2"
ubuntu-latest-arm64-vulkan-cross:
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v6
- name: Use SpacemiT Toolchain Cache
uses: actions/cache@v5
id: cache-toolchain
- uses: actions/checkout@v4
with:
path: ./spacemit_toolchain
key: spacemit-ime-toolchain-v${{ env.SPACEMIT_IME_TOOLCHAIN_VERSION }}-${{ runner.os }}
fetch-depth: 0
- name: Setup SpacemiT Toolchain
if: steps.cache-toolchain.outputs.cache-hit != 'true'
uses: ./.github/actions/linux-setup-spacemit
with:
path: ./spacemit_toolchain
version: ${{ env.SPACEMIT_IME_TOOLCHAIN_VERSION }}
- name: Setup Arm64
run: |
sudo dpkg --add-architecture arm64
sudo sed -i 's|http://azure.archive.ubuntu.com/ubuntu|http://ports.ubuntu.com/ubuntu-ports|g' \
/etc/apt/sources.list /etc/apt/apt-mirrors.txt
sudo apt-get clean
sudo apt-get update
sudo apt-get install -y --no-install-recommends \
build-essential \
glslc \
crossbuild-essential-arm64 \
libvulkan-dev:arm64 \
libcurl4-openssl-dev:arm64
- name: Build
run: |
export RISCV_ROOT_PATH=${PWD}/spacemit_toolchain
cmake -B build -DLLAMA_OPENSSL=OFF \
-DCMAKE_BUILD_TYPE=Release \
cmake -B build -DCMAKE_BUILD_TYPE=Release \
-DGGML_VULKAN=ON \
-DGGML_OPENMP=OFF \
-DLLAMA_BUILD_EXAMPLES=ON \
-DLLAMA_BUILD_TOOLS=ON \
-DLLAMA_BUILD_TESTS=OFF \
-DGGML_CPU_RISCV64_SPACEMIT=ON \
-DGGML_RVV=ON \
-DGGML_RV_ZFH=ON \
-DGGML_RV_ZICBOP=ON \
-DGGML_RV_ZIHINTPAUSE=ON \
-DRISCV64_SPACEMIT_IME_SPEC=RISCV64_SPACEMIT_IME1 \
-DCMAKE_TOOLCHAIN_FILE=${PWD}/cmake/riscv64-spacemit-linux-gnu-gcc.cmake
-DCMAKE_SYSTEM_NAME=Linux \
-DCMAKE_SYSTEM_PROCESSOR=aarch64 \
-DCMAKE_C_COMPILER=aarch64-linux-gnu-gcc \
-DCMAKE_CXX_COMPILER=aarch64-linux-gnu-g++ \
-DCMAKE_POSITION_INDEPENDENT_CODE=ON \
-DCMAKE_FIND_ROOT_PATH=/usr/lib/aarch64-linux-gnu \
-DCMAKE_FIND_ROOT_PATH_MODE_PROGRAM=NEVER \
-DCMAKE_FIND_ROOT_PATH_MODE_LIBRARY=ONLY \
-DCMAKE_FIND_ROOT_PATH_MODE_INCLUDE=BOTH
cmake --build build --config Release -j $(nproc)

File diff suppressed because it is too large Load Diff

View File

@ -1,52 +0,0 @@
name: Check vendor
on:
workflow_dispatch: # allows manual triggering
push:
branches:
- master
paths: [
'vendor/**',
'scripts/sync_vendor.py'
]
pull_request:
types: [opened, synchronize, reopened]
paths: [
'vendor/**',
'scripts/sync_vendor.py'
]
jobs:
check-vendor:
runs-on: ubuntu-slim
steps:
- name: Checkout
uses: actions/checkout@v6
with:
fetch-depth: 0
- name: Setup Python
uses: actions/setup-python@v6
with:
python-version: '3.x'
- name: Run vendor sync
run: |
set -euo pipefail
python3 scripts/sync_vendor.py
- name: Check for changes
run: |
set -euo pipefail
# detect modified or untracked files
changed=$(git status --porcelain --untracked-files=all || true)
if [ -n "$changed" ]; then
echo "Vendor sync modified files:"
echo "$changed" | awk '{ print $2 }' | sed '/^$/d'
echo "Failing because vendor files mismatch. Please update scripts/sync_vendor.py"
exit 1
else
echo "Vendor files are up-to-date."
fi

View File

@ -10,14 +10,14 @@ permissions:
jobs:
close-issues:
runs-on: ubuntu-slim
runs-on: ubuntu-latest
permissions:
issues: write
pull-requests: write
steps:
- uses: actions/stale@v10
- uses: actions/stale@v5
with:
exempt-issue-labels: "refactoring,help wanted,good first issue,research 🔬,bug,roadmap"
exempt-issue-labels: "refactor,help wanted,good first issue,research,bug,roadmap"
days-before-issue-stale: 30
days-before-issue-close: 14
stale-issue-label: "stale"

View File

@ -1,57 +0,0 @@
name: "Copilot Setup Steps"
# Automatically run the setup steps when they are changed to allow for easy validation, and
# allow manual testing through the repository's "Actions" tab
on:
workflow_dispatch:
push:
paths:
- .github/workflows/copilot-setup-steps.yml
pull_request:
paths:
- .github/workflows/copilot-setup-steps.yml
jobs:
# The job MUST be called `copilot-setup-steps` or it will not be picked up by Copilot.
copilot-setup-steps:
runs-on: ubuntu-latest
# Set the permissions to the lowest permissions possible needed for your steps.
# Copilot will be given its own token for its operations.
permissions:
# If you want to clone the repository as part of your setup steps, for example to install dependencies, you'll need the `contents: read` permission. If you don't clone the repository in your setup steps, Copilot will do this for you automatically after the steps complete.
contents: read
# You can define any steps you want, and they will run before the agent starts.
# If you do not check out your code, Copilot will do this for you.
steps:
- name: Checkout code
uses: actions/checkout@v6
- name: ccache
uses: ggml-org/ccache-action@v1.2.16
with:
key: copilot-setup-steps
evict-old-files: 1d
- name: Dependencies
id: depends
run: |
sudo apt-get update
sudo apt-get install build-essential libssl-dev
# Install git-clang-format script for formatting only changed code
wget -O /tmp/git-clang-format https://raw.githubusercontent.com/llvm/llvm-project/release/18.x/clang/tools/clang-format/git-clang-format
sudo cp /tmp/git-clang-format /usr/local/bin/git-clang-format
sudo chmod +x /usr/local/bin/git-clang-format
- name: Set up Python
uses: actions/setup-python@v6
with:
python-version: '3.11'
- name: Install Python dependencies
run: |
python3 -m venv .venv
.venv/bin/activate
pip install -r requirements/requirements-all.txt -r tools/server/tests/requirements.txt
pip install flake8 pyright pre-commit

View File

@ -28,7 +28,7 @@ jobs:
push_to_registry:
name: Push Docker image to Docker Hub
runs-on: ${{ matrix.config.runs_on }}
runs-on: ubuntu-22.04
env:
COMMIT_SHA: ${{ github.sha }}
strategy:
@ -36,25 +36,20 @@ jobs:
matrix:
config:
# Multi-stage build
# Note: the arm64 images are failing, which prevents the amd64 images from being built
# https://github.com/ggml-org/llama.cpp/issues/11888
#- { tag: "cpu", dockerfile: ".devops/cpu.Dockerfile", platforms: "linux/amd64,linux/arm64", full: true, light: true, server: true, free_disk_space: false }
- { tag: "cpu", dockerfile: ".devops/cpu.Dockerfile", platforms: "linux/amd64", full: true, light: true, server: true, free_disk_space: false, runs_on: "ubuntu-22.04" }
- { tag: "cuda cuda12", dockerfile: ".devops/cuda.Dockerfile", platforms: "linux/amd64", full: true, light: true, server: true, free_disk_space: true, runs_on: "ubuntu-22.04", cuda_version: "12.4.0", ubuntu_version: "22.04" }
- { tag: "cuda13", dockerfile: ".devops/cuda-new.Dockerfile", platforms: "linux/amd64", full: true, light: true, server: true, free_disk_space: true, runs_on: "ubuntu-22.04", cuda_version: "13.1.0", ubuntu_version: "24.04" }
- { tag: "musa", dockerfile: ".devops/musa.Dockerfile", platforms: "linux/amd64", full: true, light: true, server: true, free_disk_space: true, runs_on: "ubuntu-22.04" }
- { tag: "intel", dockerfile: ".devops/intel.Dockerfile", platforms: "linux/amd64", full: true, light: true, server: true, free_disk_space: true, runs_on: "ubuntu-22.04" }
- { tag: "vulkan", dockerfile: ".devops/vulkan.Dockerfile", platforms: "linux/amd64", full: true, light: true, server: true, free_disk_space: false, runs_on: "ubuntu-22.04" }
- { tag: "s390x", dockerfile: ".devops/s390x.Dockerfile", platforms: "linux/s390x", full: true, light: true, server: true, free_disk_space: false, runs_on: "ubuntu-22.04-s390x" }
- { tag: "rocm", dockerfile: ".devops/rocm.Dockerfile", platforms: "linux/amd64", full: true, light: true, server: true, free_disk_space: true, runs_on: "ubuntu-22.04" }
- { tag: "cpu", dockerfile: ".devops/cpu.Dockerfile", platforms: "linux/amd64,linux/arm64", full: true, light: true, server: true, free_disk_space: false }
- { tag: "cuda", dockerfile: ".devops/cuda.Dockerfile", platforms: "linux/amd64", full: true, light: true, server: true, free_disk_space: false }
- { tag: "musa", dockerfile: ".devops/musa.Dockerfile", platforms: "linux/amd64", full: true, light: true, server: true, free_disk_space: true }
- { tag: "intel", dockerfile: ".devops/intel.Dockerfile", platforms: "linux/amd64", full: true, light: true, server: true, free_disk_space: false }
- { tag: "vulkan", dockerfile: ".devops/vulkan.Dockerfile", platforms: "linux/amd64", full: true, light: true, server: true, free_disk_space: false }
# Note: the rocm images are failing due to a compiler error and are disabled until this is fixed to allow the workflow to complete
#- {tag: "rocm", dockerfile: ".devops/rocm.Dockerfile", platforms: "linux/amd64,linux/arm64", full: true, light: true, server: true, free_disk_space: true }
steps:
- name: Check out the repo
uses: actions/checkout@v6
uses: actions/checkout@v4
with:
fetch-depth: 0 # preserve git history, so we can determine the build number
- name: Set up QEMU
if: ${{ matrix.config.tag != 's390x' }}
uses: docker/setup-qemu-action@v3
with:
image: tonistiigi/binfmt:qemu-v7.0.0-28
@ -63,48 +58,46 @@ jobs:
uses: docker/setup-buildx-action@v3
- name: Log in to Docker Hub
uses: docker/login-action@v3
uses: docker/login-action@v2
with:
registry: ghcr.io
username: ${{ github.repository_owner }}
password: ${{ secrets.GITHUB_TOKEN }}
- name: Determine source tag name
id: srctag
uses: ./.github/actions/get-tag-name
env:
BRANCH_NAME: ${{ github.head_ref || github.ref_name }}
- name: Determine image tag name
- name: Determine tag name
id: tag
shell: bash
run: |
BUILD_NUMBER="$(git rev-list --count HEAD)"
SHORT_HASH="$(git rev-parse --short=7 HEAD)"
REPO_OWNER="${GITHUB_REPOSITORY_OWNER@L}" # to lower case
REPO_NAME="${{ github.event.repository.name }}"
PREFIX="ghcr.io/${REPO_OWNER}/${REPO_NAME}:"
# determine tag name postfix (build number, commit hash)
if [[ "${{ env.GITHUB_BRANCH_NAME }}" == "master" ]]; then
TAG_POSTFIX="-b${BUILD_NUMBER}"
else
SAFE_NAME=$(echo "${{ env.GITHUB_BRANCH_NAME }}" | tr '/' '-')
TAG_POSTFIX="-${SAFE_NAME}-${SHORT_HASH}"
fi
# list all tags possible
tags="${{ matrix.config.tag }}"
for tag in $tags; do
if [[ "$tag" == "cpu" ]]; then
TYPE=""
else
TYPE="-$tag"
fi
CACHETAGS="${PREFIX}buildcache${TYPE}"
FULLTAGS="${FULLTAGS:+$FULLTAGS,}${PREFIX}full${TYPE},${PREFIX}full${TYPE}-${{ steps.srctag.outputs.name }}"
LIGHTTAGS="${LIGHTTAGS:+$LIGHTTAGS,}${PREFIX}light${TYPE},${PREFIX}light${TYPE}-${{ steps.srctag.outputs.name }}"
SERVERTAGS="${SERVERTAGS:+$SERVERTAGS,}${PREFIX}server${TYPE},${PREFIX}server${TYPE}-${{ steps.srctag.outputs.name }}"
done
echo "cache_output_tags=$CACHETAGS" >> $GITHUB_OUTPUT
if [[ "${{ matrix.config.tag }}" == "cpu" ]]; then
TYPE=""
else
TYPE="-${{ matrix.config.tag }}"
fi
PREFIX="ghcr.io/${REPO_OWNER}/${REPO_NAME}:"
FULLTAGS="${PREFIX}full${TYPE},${PREFIX}full${TYPE}${TAG_POSTFIX}"
LIGHTTAGS="${PREFIX}light${TYPE},${PREFIX}light${TYPE}${TAG_POSTFIX}"
SERVERTAGS="${PREFIX}server${TYPE},${PREFIX}server${TYPE}${TAG_POSTFIX}"
echo "full_output_tags=$FULLTAGS" >> $GITHUB_OUTPUT
echo "light_output_tags=$LIGHTTAGS" >> $GITHUB_OUTPUT
echo "server_output_tags=$SERVERTAGS" >> $GITHUB_OUTPUT
echo "cache_output_tags=$CACHETAGS" # print out for debugging
echo "full_output_tags=$FULLTAGS" # print out for debugging
echo "light_output_tags=$LIGHTTAGS" # print out for debugging
echo "server_output_tags=$SERVERTAGS" # print out for debugging
env:
GITHUB_BRANCH_NAME: ${{ github.head_ref || github.ref_name }}
GITHUB_REPOSITORY_OWNER: '${{ github.repository_owner }}'
- name: Free Disk Space (Ubuntu)
@ -136,18 +129,12 @@ jobs:
file: ${{ matrix.config.dockerfile }}
target: full
provenance: false
build-args: |
${{ matrix.config.ubuntu_version && format('UBUNTU_VERSION={0}', matrix.config.ubuntu_version) || '' }}
${{ matrix.config.cuda_version && format('CUDA_VERSION={0}', matrix.config.cuda_version) || '' }}
# using github experimental cache
#cache-from: type=gha
#cache-to: type=gha,mode=max
cache-from: type=gha
cache-to: type=gha,mode=max
# return to this if the experimental github cache is having issues
#cache-to: type=local,dest=/tmp/.buildx-cache
#cache-from: type=local,src=/tmp/.buildx-cache
# using registry cache (no storage limit)
cache-from: type=registry,ref=${{ steps.tag.outputs.cache_output_tags }}
cache-to: type=registry,ref=${{ steps.tag.outputs.cache_output_tags }},mode=max
- name: Build and push Light Docker image (tagged + versioned)
if: ${{ (github.event_name == 'push' || github.event_name == 'schedule' || github.event_name == 'workflow_dispatch') && matrix.config.light == true }}
@ -161,18 +148,12 @@ jobs:
file: ${{ matrix.config.dockerfile }}
target: light
provenance: false
build-args: |
${{ matrix.config.ubuntu_version && format('UBUNTU_VERSION={0}', matrix.config.ubuntu_version) || '' }}
${{ matrix.config.cuda_version && format('CUDA_VERSION={0}', matrix.config.cuda_version) || '' }}
# using github experimental cache
#cache-from: type=gha
#cache-to: type=gha,mode=max
cache-from: type=gha
cache-to: type=gha,mode=max
# return to this if the experimental github cache is having issues
#cache-to: type=local,dest=/tmp/.buildx-cache
#cache-from: type=local,src=/tmp/.buildx-cache
# using registry cache (no storage limit)
cache-from: type=registry,ref=${{ steps.tag.outputs.cache_output_tags }}
cache-to: type=registry,ref=${{ steps.tag.outputs.cache_output_tags }},mode=max
- name: Build and push Server Docker image (tagged + versioned)
if: ${{ (github.event_name == 'push' || github.event_name == 'schedule' || github.event_name == 'workflow_dispatch') && matrix.config.server == true }}
@ -186,41 +167,9 @@ jobs:
file: ${{ matrix.config.dockerfile }}
target: server
provenance: false
build-args: |
${{ matrix.config.ubuntu_version && format('UBUNTU_VERSION={0}', matrix.config.ubuntu_version) || '' }}
${{ matrix.config.cuda_version && format('CUDA_VERSION={0}', matrix.config.cuda_version) || '' }}
# using github experimental cache
#cache-from: type=gha
#cache-to: type=gha,mode=max
cache-from: type=gha
cache-to: type=gha,mode=max
# return to this if the experimental github cache is having issues
#cache-to: type=local,dest=/tmp/.buildx-cache
#cache-from: type=local,src=/tmp/.buildx-cache
# using registry cache (no storage limit)
cache-from: type=registry,ref=${{ steps.tag.outputs.cache_output_tags }}
cache-to: type=registry,ref=${{ steps.tag.outputs.cache_output_tags }},mode=max
create_tag:
name: Create and push git tag
runs-on: ubuntu-22.04
permissions:
contents: write
steps:
- name: Clone
id: checkout
uses: actions/checkout@v6
with:
fetch-depth: 0
- name: Determine source tag name
id: srctag
uses: ./.github/actions/get-tag-name
env:
BRANCH_NAME: ${{ github.head_ref || github.ref_name }}
- name: Create and push git tag
env:
GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
run: |
git tag ${{ steps.srctag.outputs.name }} || exit 0
git push origin ${{ steps.srctag.outputs.name }} || exit 0

View File

@ -20,9 +20,9 @@ concurrency:
jobs:
editorconfig:
runs-on: ubuntu-slim
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v6
- uses: actions/checkout@v4
- uses: editorconfig-checker/action-editorconfig-checker@v2
with:
version: v3.0.3

View File

@ -21,12 +21,12 @@ on:
jobs:
deploy:
runs-on: ubuntu-slim
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v6
- uses: actions/checkout@v4
- name: Set up Python
uses: actions/setup-python@v6
uses: actions/setup-python@v5
with:
python-version: '3.9.x'
- name: Install dependencies

View File

@ -7,11 +7,11 @@ jobs:
permissions:
contents: read
pull-requests: write
runs-on: ubuntu-slim
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v6
- uses: actions/checkout@v4
with:
repository: "ggml-org/llama.cpp"
- uses: actions/labeler@v6
- uses: actions/labeler@v5
with:
configuration-path: '.github/labeler.yml'

View File

@ -1,45 +0,0 @@
name: Check Pre-Tokenizer Hashes
on:
push:
paths:
- 'convert_hf_to_gguf.py'
- 'convert_hf_to_gguf_update.py'
pull_request:
paths:
- 'convert_hf_to_gguf.py'
- 'convert_hf_to_gguf_update.py'
jobs:
pre-tokenizer-hashes:
runs-on: ubuntu-slim
steps:
- name: Checkout repository
uses: actions/checkout@v6
- name: Set up Python
uses: actions/setup-python@v6
with:
python-version: '3.11'
- name: Install Python dependencies
run: |
python3 -m venv .venv
.venv/bin/pip install -r requirements/requirements-convert_hf_to_gguf_update.txt
- name: Update pre-tokenizer hashes
run: |
cp convert_hf_to_gguf.py /tmp
.venv/bin/python convert_hf_to_gguf_update.py --check-missing
- name: Check if committed pre-tokenizer hashes matches generated version
run: |
if ! diff -q convert_hf_to_gguf.py /tmp/convert_hf_to_gguf.py; then
echo "Model pre-tokenizer hashes (in convert_hf_to_gguf.py) do not match generated hashes (from convert_hf_to_gguf_update.py)."
echo "To fix: run ./convert_hf_to_gguf_update.py and commit the updated convert_hf_to_gguf.py along with your changes"
echo "Differences found:"
diff convert_hf_to_gguf.py /tmp/convert_hf_to_gguf.py || true
exit 1
fi
echo "Model pre-tokenizer hashes are up to date."

View File

@ -20,13 +20,13 @@ concurrency:
jobs:
python-check-requirements:
runs-on: ubuntu-slim
runs-on: ubuntu-latest
name: check-requirements
steps:
- name: Check out source repository
uses: actions/checkout@v6
uses: actions/checkout@v4
- name: Set up Python environment
uses: actions/setup-python@v6
uses: actions/setup-python@v5
with:
python-version: "3.11"
- name: Run check-requirements.sh script

View File

@ -15,13 +15,13 @@ concurrency:
jobs:
flake8-lint:
runs-on: ubuntu-slim
runs-on: ubuntu-latest
name: Lint
steps:
- name: Check out source repository
uses: actions/checkout@v6
uses: actions/checkout@v4
- name: Set up Python environment
uses: actions/setup-python@v6
uses: actions/setup-python@v5
with:
python-version: "3.11"
- name: flake8 Lint

View File

@ -24,12 +24,14 @@ jobs:
name: pyright type-check
steps:
- name: Check out source repository
uses: actions/checkout@v6
uses: actions/checkout@v4
- name: Set up Python environment
uses: actions/setup-python@v6
uses: actions/setup-python@v5
with:
python-version: "3.11"
pip-install: -r requirements/requirements-all.txt
- name: Install Python dependencies
# TODO: use a venv
run: pip install -r requirements/requirements-all.txt
- name: Type-check with Pyright
uses: jakebailey/pyright-action@v2
with:

View File

@ -1,908 +0,0 @@
name: Release
on:
workflow_dispatch: # allows manual triggering
inputs:
create_release:
description: 'Create new release'
required: true
type: boolean
push:
branches:
- master
paths: ['.github/workflows/release.yml', '**/CMakeLists.txt', '**/.cmake', '**/*.h', '**/*.hpp', '**/*.c', '**/*.cpp', '**/*.cu', '**/*.cuh', '**/*.swift', '**/*.m', '**/*.metal', '**/*.comp']
concurrency:
group: ${{ github.workflow }}-${{ github.head_ref && github.ref || github.run_id }}
cancel-in-progress: true
env:
BRANCH_NAME: ${{ github.head_ref || github.ref_name }}
CMAKE_ARGS: "-DLLAMA_BUILD_EXAMPLES=OFF -DLLAMA_BUILD_TESTS=OFF -DLLAMA_BUILD_TOOLS=ON -DLLAMA_BUILD_SERVER=ON -DGGML_RPC=ON"
jobs:
macOS-arm64:
runs-on: macos-14
steps:
- name: Clone
id: checkout
uses: actions/checkout@v6
with:
fetch-depth: 0
- name: ccache
uses: ggml-org/ccache-action@v1.2.16
with:
key: macOS-latest-cmake-arm64
evict-old-files: 1d
- name: Build
id: cmake_build
run: |
sysctl -a
cmake -B build \
-DCMAKE_INSTALL_RPATH='@loader_path' \
-DCMAKE_BUILD_WITH_INSTALL_RPATH=ON \
-DLLAMA_FATAL_WARNINGS=ON \
-DLLAMA_BUILD_BORINGSSL=ON \
-DGGML_METAL_USE_BF16=ON \
-DGGML_METAL_EMBED_LIBRARY=ON \
-DGGML_RPC=ON \
${{ env.CMAKE_ARGS }}
cmake --build build --config Release -j $(sysctl -n hw.logicalcpu)
- name: Determine tag name
id: tag
uses: ./.github/actions/get-tag-name
- name: Pack artifacts
id: pack_artifacts
run: |
cp LICENSE ./build/bin/
tar -czvf llama-${{ steps.tag.outputs.name }}-bin-macos-arm64.tar.gz -s ",./,llama-${{ steps.tag.outputs.name }}/," -C ./build/bin .
- name: Upload artifacts
uses: actions/upload-artifact@v6
with:
path: llama-${{ steps.tag.outputs.name }}-bin-macos-arm64.tar.gz
name: llama-bin-macos-arm64.tar.gz
macOS-x64:
runs-on: macos-15-intel
steps:
- name: Clone
id: checkout
uses: actions/checkout@v6
with:
fetch-depth: 0
- name: ccache
uses: ggml-org/ccache-action@v1.2.16
with:
key: macOS-latest-cmake-x64
evict-old-files: 1d
- name: Build
id: cmake_build
run: |
sysctl -a
# Metal is disabled due to intermittent failures with Github runners not having a GPU:
# https://github.com/ggml-org/llama.cpp/actions/runs/8635935781/job/23674807267#step:5:2313
cmake -B build \
-DCMAKE_INSTALL_RPATH='@loader_path' \
-DCMAKE_BUILD_WITH_INSTALL_RPATH=ON \
-DLLAMA_FATAL_WARNINGS=ON \
-DLLAMA_BUILD_BORINGSSL=ON \
-DGGML_METAL=OFF \
-DGGML_RPC=ON \
-DCMAKE_OSX_DEPLOYMENT_TARGET=13.3
cmake --build build --config Release -j $(sysctl -n hw.logicalcpu)
- name: Determine tag name
id: tag
uses: ./.github/actions/get-tag-name
- name: Pack artifacts
id: pack_artifacts
run: |
cp LICENSE ./build/bin/
tar -czvf llama-${{ steps.tag.outputs.name }}-bin-macos-x64.tar.gz -s ",./,llama-${{ steps.tag.outputs.name }}/," -C ./build/bin .
- name: Upload artifacts
uses: actions/upload-artifact@v6
with:
path: llama-${{ steps.tag.outputs.name }}-bin-macos-x64.tar.gz
name: llama-bin-macos-x64.tar.gz
ubuntu-22-cpu:
strategy:
matrix:
include:
- build: 'x64'
os: ubuntu-22.04
- build: 's390x'
os: ubuntu-24.04-s390x
# GGML_BACKEND_DL and GGML_CPU_ALL_VARIANTS are not currently supported on arm
# - build: 'arm64'
# os: ubuntu-22.04-arm
runs-on: ${{ matrix.os }}
steps:
- name: Clone
id: checkout
uses: actions/checkout@v6
with:
fetch-depth: 0
- name: ccache
uses: ggml-org/ccache-action@v1.2.16
with:
key: ubuntu-cpu-cmake-${{ matrix.build }}
evict-old-files: 1d
- name: Dependencies
id: depends
run: |
sudo apt-get update
sudo apt-get install build-essential libssl-dev
- name: Build
id: cmake_build
run: |
cmake -B build \
-DCMAKE_INSTALL_RPATH='$ORIGIN' \
-DCMAKE_BUILD_WITH_INSTALL_RPATH=ON \
-DGGML_BACKEND_DL=ON \
-DGGML_NATIVE=OFF \
-DGGML_CPU_ALL_VARIANTS=ON \
-DLLAMA_FATAL_WARNINGS=ON \
${{ env.CMAKE_ARGS }}
cmake --build build --config Release -j $(nproc)
- name: Determine tag name
id: tag
uses: ./.github/actions/get-tag-name
- name: Pack artifacts
id: pack_artifacts
run: |
cp LICENSE ./build/bin/
tar -czvf llama-${{ steps.tag.outputs.name }}-bin-ubuntu-${{ matrix.build }}.tar.gz --transform "s,./,llama-${{ steps.tag.outputs.name }}/," -C ./build/bin .
- name: Upload artifacts
uses: actions/upload-artifact@v6
with:
path: llama-${{ steps.tag.outputs.name }}-bin-ubuntu-${{ matrix.build }}.tar.gz
name: llama-bin-ubuntu-${{ matrix.build }}.tar.gz
ubuntu-22-vulkan:
runs-on: ubuntu-22.04
steps:
- name: Clone
id: checkout
uses: actions/checkout@v6
with:
fetch-depth: 0
- name: ccache
uses: ggml-org/ccache-action@v1.2.16
with:
key: ubuntu-22-cmake-vulkan
evict-old-files: 1d
- name: Dependencies
id: depends
run: |
wget -qO - https://packages.lunarg.com/lunarg-signing-key-pub.asc | sudo apt-key add -
sudo wget -qO /etc/apt/sources.list.d/lunarg-vulkan-jammy.list https://packages.lunarg.com/vulkan/lunarg-vulkan-jammy.list
sudo apt-get update -y
sudo apt-get install -y build-essential mesa-vulkan-drivers vulkan-sdk libssl-dev
- name: Build
id: cmake_build
run: |
cmake -B build \
-DCMAKE_INSTALL_RPATH='$ORIGIN' \
-DCMAKE_BUILD_WITH_INSTALL_RPATH=ON \
-DGGML_BACKEND_DL=ON \
-DGGML_NATIVE=OFF \
-DGGML_CPU_ALL_VARIANTS=ON \
-DGGML_VULKAN=ON \
${{ env.CMAKE_ARGS }}
cmake --build build --config Release -j $(nproc)
- name: Determine tag name
id: tag
uses: ./.github/actions/get-tag-name
- name: Pack artifacts
id: pack_artifacts
run: |
cp LICENSE ./build/bin/
tar -czvf llama-${{ steps.tag.outputs.name }}-bin-ubuntu-vulkan-x64.tar.gz --transform "s,./,llama-${{ steps.tag.outputs.name }}/," -C ./build/bin .
- name: Upload artifacts
uses: actions/upload-artifact@v6
with:
path: llama-${{ steps.tag.outputs.name }}-bin-ubuntu-vulkan-x64.tar.gz
name: llama-bin-ubuntu-vulkan-x64.tar.gz
windows-cpu:
runs-on: windows-2025
strategy:
matrix:
include:
- arch: 'x64'
- arch: 'arm64'
steps:
- name: Clone
uses: actions/checkout@v6
with:
fetch-depth: 0
- name: ccache
uses: ggml-org/ccache-action@v1.2.16
with:
key: windows-latest-cmake-cpu-${{ matrix.arch }}
variant: ccache
evict-old-files: 1d
- name: Install Ninja
run: |
choco install ninja
- name: Build
shell: cmd
run: |
call "C:\Program Files\Microsoft Visual Studio\2022\Enterprise\VC\Auxiliary\Build\vcvarsall.bat" ${{ matrix.arch == 'x64' && 'x64' || 'amd64_arm64' }}
cmake -S . -B build -G "Ninja Multi-Config" ^
-D CMAKE_TOOLCHAIN_FILE=cmake/${{ matrix.arch }}-windows-llvm.cmake ^
-DLLAMA_BUILD_BORINGSSL=ON ^
-DGGML_NATIVE=OFF ^
-DGGML_BACKEND_DL=ON ^
-DGGML_CPU_ALL_VARIANTS=${{ matrix.arch == 'x64' && 'ON' || 'OFF' }} ^
-DGGML_OPENMP=ON ^
${{ env.CMAKE_ARGS }}
cmake --build build --config Release
- name: Pack artifacts
id: pack_artifacts
run: |
Copy-Item "C:\Program Files\Microsoft Visual Studio\2022\Enterprise\VC\Redist\MSVC\14.44.35112\debug_nonredist\${{ matrix.arch }}\Microsoft.VC143.OpenMP.LLVM\libomp140.${{ matrix.arch == 'x64' && 'x86_64' || 'aarch64' }}.dll" .\build\bin\Release\
7z a -snl llama-bin-win-cpu-${{ matrix.arch }}.zip .\build\bin\Release\*
- name: Upload artifacts
uses: actions/upload-artifact@v6
with:
path: llama-bin-win-cpu-${{ matrix.arch }}.zip
name: llama-bin-win-cpu-${{ matrix.arch }}.zip
windows:
runs-on: windows-2025
env:
OPENBLAS_VERSION: 0.3.23
VULKAN_VERSION: 1.4.313.2
strategy:
matrix:
include:
- backend: 'vulkan'
arch: 'x64'
defines: '-DGGML_VULKAN=ON'
target: 'ggml-vulkan'
- backend: 'opencl-adreno'
arch: 'arm64'
defines: '-G "Ninja Multi-Config" -D CMAKE_TOOLCHAIN_FILE=cmake/arm64-windows-llvm.cmake -DCMAKE_PREFIX_PATH="$env:RUNNER_TEMP/opencl-arm64-release" -DGGML_OPENCL=ON -DGGML_OPENCL_USE_ADRENO_KERNELS=ON'
target: 'ggml-opencl'
steps:
- name: Clone
id: checkout
uses: actions/checkout@v6
- name: ccache
uses: ggml-org/ccache-action@v1.2.16
with:
key: windows-latest-cmake-${{ matrix.backend }}-${{ matrix.arch }}
variant: ccache
evict-old-files: 1d
- name: Install Vulkan SDK
id: get_vulkan
if: ${{ matrix.backend == 'vulkan' }}
run: |
curl.exe -o $env:RUNNER_TEMP/VulkanSDK-Installer.exe -L "https://sdk.lunarg.com/sdk/download/${env:VULKAN_VERSION}/windows/vulkansdk-windows-X64-${env:VULKAN_VERSION}.exe"
& "$env:RUNNER_TEMP\VulkanSDK-Installer.exe" --accept-licenses --default-answer --confirm-command install
Add-Content $env:GITHUB_ENV "VULKAN_SDK=C:\VulkanSDK\${env:VULKAN_VERSION}"
Add-Content $env:GITHUB_PATH "C:\VulkanSDK\${env:VULKAN_VERSION}\bin"
- name: Install Ninja
id: install_ninja
run: |
choco install ninja
- name: Install OpenCL Headers and Libs
id: install_opencl
if: ${{ matrix.backend == 'opencl-adreno' && matrix.arch == 'arm64' }}
run: |
git clone https://github.com/KhronosGroup/OpenCL-Headers
cd OpenCL-Headers
cmake -B build `
-DBUILD_TESTING=OFF `
-DOPENCL_HEADERS_BUILD_TESTING=OFF `
-DOPENCL_HEADERS_BUILD_CXX_TESTS=OFF `
-DCMAKE_INSTALL_PREFIX="$env:RUNNER_TEMP/opencl-arm64-release"
cmake --build build --target install
git clone https://github.com/KhronosGroup/OpenCL-ICD-Loader
cd OpenCL-ICD-Loader
cmake -B build-arm64-release `
-A arm64 `
-DCMAKE_PREFIX_PATH="$env:RUNNER_TEMP/opencl-arm64-release" `
-DCMAKE_INSTALL_PREFIX="$env:RUNNER_TEMP/opencl-arm64-release"
cmake --build build-arm64-release --target install --config release
- name: Build
id: cmake_build
run: |
cmake -S . -B build ${{ matrix.defines }} -DGGML_NATIVE=OFF -DGGML_CPU=OFF -DGGML_BACKEND_DL=ON -DLLAMA_BUILD_BORINGSSL=ON
cmake --build build --config Release --target ${{ matrix.target }}
- name: Pack artifacts
id: pack_artifacts
run: |
7z a -snl llama-bin-win-${{ matrix.backend }}-${{ matrix.arch }}.zip .\build\bin\Release\${{ matrix.target }}.dll
- name: Upload artifacts
uses: actions/upload-artifact@v6
with:
path: llama-bin-win-${{ matrix.backend }}-${{ matrix.arch }}.zip
name: llama-bin-win-${{ matrix.backend }}-${{ matrix.arch }}.zip
windows-cuda:
runs-on: windows-2022
strategy:
matrix:
cuda: ['12.4', '13.1']
steps:
- name: Clone
id: checkout
uses: actions/checkout@v6
- name: Install ccache
uses: ggml-org/ccache-action@v1.2.16
with:
key: windows-cuda-${{ matrix.cuda }}
variant: ccache
evict-old-files: 1d
- name: Install Cuda Toolkit
uses: ./.github/actions/windows-setup-cuda
with:
cuda_version: ${{ matrix.cuda }}
- name: Install Ninja
id: install_ninja
run: |
choco install ninja
- name: Build
id: cmake_build
shell: cmd
# TODO: Remove GGML_CUDA_CUB_3DOT2 flag once CCCL 3.2 is bundled within CTK and that CTK version is used in this project
run: |
call "C:\Program Files\Microsoft Visual Studio\2022\Enterprise\VC\Auxiliary\Build\vcvarsall.bat" x64
cmake -S . -B build -G "Ninja Multi-Config" ^
-DGGML_BACKEND_DL=ON ^
-DGGML_NATIVE=OFF ^
-DGGML_CPU=OFF ^
-DGGML_CUDA=ON ^
-DLLAMA_BUILD_BORINGSSL=ON ^
-DGGML_CUDA_CUB_3DOT2=ON
set /A NINJA_JOBS=%NUMBER_OF_PROCESSORS%-1
cmake --build build --config Release -j %NINJA_JOBS% --target ggml-cuda
- name: Pack artifacts
id: pack_artifacts
run: |
7z a -snl llama-bin-win-cuda-${{ matrix.cuda }}-x64.zip .\build\bin\Release\ggml-cuda.dll
- name: Upload artifacts
uses: actions/upload-artifact@v6
with:
path: llama-bin-win-cuda-${{ matrix.cuda }}-x64.zip
name: llama-bin-win-cuda-${{ matrix.cuda }}-x64.zip
- name: Copy and pack Cuda runtime
run: |
echo "Cuda install location: ${{ env.CUDA_PATH }}"
$dst='.\build\bin\cudart\'
robocopy "${{env.CUDA_PATH}}\bin" $dst cudart64_*.dll cublas64_*.dll cublasLt64_*.dll
robocopy "${{env.CUDA_PATH}}\lib" $dst cudart64_*.dll cublas64_*.dll cublasLt64_*.dll
robocopy "${{env.CUDA_PATH}}\bin\x64" $dst cudart64_*.dll cublas64_*.dll cublasLt64_*.dll
7z a cudart-llama-bin-win-cuda-${{ matrix.cuda }}-x64.zip $dst\*
- name: Upload Cuda runtime
uses: actions/upload-artifact@v6
with:
path: cudart-llama-bin-win-cuda-${{ matrix.cuda }}-x64.zip
name: cudart-llama-bin-win-cuda-${{ matrix.cuda }}-x64.zip
windows-sycl:
runs-on: windows-2022
defaults:
run:
shell: bash
env:
WINDOWS_BASEKIT_URL: https://registrationcenter-download.intel.com/akdlm/IRC_NAS/24751ead-ddc5-4479-b9e6-f9fe2ff8b9f2/intel-deep-learning-essentials-2025.2.1.25_offline.exe
WINDOWS_DPCPP_MKL: intel.oneapi.win.cpp-dpcpp-common:intel.oneapi.win.mkl.devel:intel.oneapi.win.dnnl:intel.oneapi.win.tbb.devel
ONEAPI_ROOT: "C:/Program Files (x86)/Intel/oneAPI"
steps:
- name: Clone
id: checkout
uses: actions/checkout@v6
- name: ccache
uses: ggml-org/ccache-action@v1.2.16
with:
key: windows-latest-cmake-sycl
variant: ccache
evict-old-files: 1d
- name: Install
run: |
scripts/install-oneapi.bat $WINDOWS_BASEKIT_URL $WINDOWS_DPCPP_MKL
- name: Build
id: cmake_build
shell: cmd
run: |
call "C:\Program Files (x86)\Intel\oneAPI\setvars.bat" intel64 --force
cmake -G "Ninja" -B build ^
-DCMAKE_C_COMPILER=cl -DCMAKE_CXX_COMPILER=icx ^
-DCMAKE_BUILD_TYPE=Release ^
-DGGML_BACKEND_DL=ON -DBUILD_SHARED_LIBS=ON ^
-DGGML_CPU=OFF -DGGML_SYCL=ON ^
-DLLAMA_BUILD_BORINGSSL=ON
cmake --build build --target ggml-sycl -j
- name: Build the release package
id: pack_artifacts
run: |
echo "cp oneAPI running time dll files in ${{ env.ONEAPI_ROOT }} to ./build/bin"
cp "${{ env.ONEAPI_ROOT }}/mkl/latest/bin/mkl_sycl_blas.5.dll" ./build/bin
cp "${{ env.ONEAPI_ROOT }}/mkl/latest/bin/mkl_core.2.dll" ./build/bin
cp "${{ env.ONEAPI_ROOT }}/mkl/latest/bin/mkl_tbb_thread.2.dll" ./build/bin
cp "${{ env.ONEAPI_ROOT }}/compiler/latest/bin/ur_adapter_level_zero.dll" ./build/bin
cp "${{ env.ONEAPI_ROOT }}/compiler/latest/bin/ur_adapter_level_zero_v2.dll" ./build/bin
cp "${{ env.ONEAPI_ROOT }}/compiler/latest/bin/ur_adapter_opencl.dll" ./build/bin
cp "${{ env.ONEAPI_ROOT }}/compiler/latest/bin/ur_loader.dll" ./build/bin
cp "${{ env.ONEAPI_ROOT }}/compiler/latest/bin/ur_win_proxy_loader.dll" ./build/bin
cp "${{ env.ONEAPI_ROOT }}/compiler/latest/bin/sycl8.dll" ./build/bin
cp "${{ env.ONEAPI_ROOT }}/compiler/latest/bin/svml_dispmd.dll" ./build/bin
cp "${{ env.ONEAPI_ROOT }}/compiler/latest/bin/libmmd.dll" ./build/bin
cp "${{ env.ONEAPI_ROOT }}/compiler/latest/bin/libiomp5md.dll" ./build/bin
cp "${{ env.ONEAPI_ROOT }}/compiler/latest/bin/sycl-ls.exe" ./build/bin
cp "${{ env.ONEAPI_ROOT }}/compiler/latest/bin/libsycl-fallback-bfloat16.spv" ./build/bin
cp "${{ env.ONEAPI_ROOT }}/compiler/latest/bin/libsycl-native-bfloat16.spv" ./build/bin
cp "${{ env.ONEAPI_ROOT }}/dnnl/latest/bin/dnnl.dll" ./build/bin
cp "${{ env.ONEAPI_ROOT }}/tbb/latest/bin/tbb12.dll" ./build/bin
cp "${{ env.ONEAPI_ROOT }}/tcm/latest/bin/tcm.dll" ./build/bin
cp "${{ env.ONEAPI_ROOT }}/tcm/latest/bin/libhwloc-15.dll" ./build/bin
cp "${{ env.ONEAPI_ROOT }}/umf/latest/bin/umf.dll" ./build/bin
echo "cp oneAPI running time dll files to ./build/bin done"
7z a -snl llama-bin-win-sycl-x64.zip ./build/bin/*
- name: Upload the release package
uses: actions/upload-artifact@v6
with:
path: llama-bin-win-sycl-x64.zip
name: llama-bin-win-sycl-x64.zip
windows-hip:
runs-on: windows-2022
env:
HIPSDK_INSTALLER_VERSION: "25.Q3"
strategy:
matrix:
include:
- name: "radeon"
gpu_targets: "gfx1151;gfx1200;gfx1201;gfx1100;gfx1101;gfx1102;gfx1030;gfx1031;gfx1032"
steps:
- name: Clone
id: checkout
uses: actions/checkout@v6
- name: Grab rocWMMA package
id: grab_rocwmma
run: |
curl -o rocwmma.deb "https://repo.radeon.com/rocm/apt/7.0.1/pool/main/r/rocwmma-dev/rocwmma-dev_2.0.0.70001-42~24.04_amd64.deb"
7z x rocwmma.deb
7z x data.tar
- name: Cache ROCm Installation
id: cache-rocm
uses: actions/cache@v5
with:
path: C:\Program Files\AMD\ROCm
key: rocm-${{ env.HIPSDK_INSTALLER_VERSION }}-${{ runner.os }}
- name: ccache
uses: ggml-org/ccache-action@v1.2.16
with:
key: windows-latest-cmake-hip-${{ env.HIPSDK_INSTALLER_VERSION }}-${{ matrix.name }}-x64
evict-old-files: 1d
- name: Install ROCm
if: steps.cache-rocm.outputs.cache-hit != 'true'
id: depends
run: |
$ErrorActionPreference = "Stop"
write-host "Downloading AMD HIP SDK Installer"
Invoke-WebRequest -Uri "https://download.amd.com/developer/eula/rocm-hub/AMD-Software-PRO-Edition-${{ env.HIPSDK_INSTALLER_VERSION }}-WinSvr2022-For-HIP.exe" -OutFile "${env:RUNNER_TEMP}\rocm-install.exe"
write-host "Installing AMD HIP SDK"
$proc = Start-Process "${env:RUNNER_TEMP}\rocm-install.exe" -ArgumentList '-install' -NoNewWindow -PassThru
$completed = $proc.WaitForExit(600000)
if (-not $completed) {
Write-Error "ROCm installation timed out after 10 minutes. Killing the process"
$proc.Kill()
exit 1
}
if ($proc.ExitCode -ne 0) {
Write-Error "ROCm installation failed with exit code $($proc.ExitCode)"
exit 1
}
write-host "Completed AMD HIP SDK installation"
- name: Verify ROCm
id: verify
run: |
# Find and test ROCm installation
$clangPath = Get-ChildItem 'C:\Program Files\AMD\ROCm\*\bin\clang.exe' | Select-Object -First 1
if (-not $clangPath) {
Write-Error "ROCm installation not found"
exit 1
}
& $clangPath.FullName --version
- name: Build
id: cmake_build
run: |
$env:HIP_PATH=$(Resolve-Path 'C:\Program Files\AMD\ROCm\*\bin\clang.exe' | split-path | split-path)
$env:CMAKE_PREFIX_PATH="${env:HIP_PATH}"
cmake -G "Unix Makefiles" -B build -S . `
-DCMAKE_C_COMPILER="${env:HIP_PATH}\bin\clang.exe" `
-DCMAKE_CXX_COMPILER="${env:HIP_PATH}\bin\clang++.exe" `
-DCMAKE_CXX_FLAGS="-I$($PWD.Path.Replace('\', '/'))/opt/rocm-7.0.1/include/ -Wno-ignored-attributes -Wno-nested-anon-types" `
-DCMAKE_BUILD_TYPE=Release `
-DGGML_BACKEND_DL=ON `
-DGGML_NATIVE=OFF `
-DGGML_CPU=OFF `
-DAMDGPU_TARGETS="${{ matrix.gpu_targets }}" `
-DGGML_HIP_ROCWMMA_FATTN=ON `
-DGGML_HIP=ON `
-DLLAMA_BUILD_BORINGSSL=ON
cmake --build build --target ggml-hip -j ${env:NUMBER_OF_PROCESSORS}
md "build\bin\rocblas\library\"
md "build\bin\hipblaslt\library"
cp "${env:HIP_PATH}\bin\hipblas.dll" "build\bin\"
cp "${env:HIP_PATH}\bin\hipblaslt.dll" "build\bin\"
cp "${env:HIP_PATH}\bin\rocblas.dll" "build\bin\"
cp "${env:HIP_PATH}\bin\rocblas\library\*" "build\bin\rocblas\library\"
cp "${env:HIP_PATH}\bin\hipblaslt\library\*" "build\bin\hipblaslt\library\"
- name: Pack artifacts
id: pack_artifacts
run: |
7z a -snl llama-bin-win-hip-${{ matrix.name }}-x64.zip .\build\bin\*
- name: Upload artifacts
uses: actions/upload-artifact@v6
with:
path: llama-bin-win-hip-${{ matrix.name }}-x64.zip
name: llama-bin-win-hip-${{ matrix.name }}-x64.zip
ios-xcode-build:
runs-on: macos-15
steps:
- name: Checkout code
uses: actions/checkout@v6
with:
fetch-depth: 0
- name: Setup Xcode
run: |
sudo xcode-select -s /Applications/Xcode_16.4.app
- name: Build
id: cmake_build
run: |
sysctl -a
cmake -B build -G Xcode \
-DGGML_METAL_USE_BF16=ON \
-DGGML_METAL_EMBED_LIBRARY=ON \
-DLLAMA_OPENSSL=OFF \
-DLLAMA_BUILD_EXAMPLES=OFF \
-DLLAMA_BUILD_TOOLS=OFF \
-DLLAMA_BUILD_TESTS=OFF \
-DLLAMA_BUILD_SERVER=OFF \
-DCMAKE_SYSTEM_NAME=iOS \
-DCMAKE_OSX_DEPLOYMENT_TARGET=14.0 \
-DCMAKE_XCODE_ATTRIBUTE_DEVELOPMENT_TEAM=ggml
cmake --build build --config Release -j $(sysctl -n hw.logicalcpu) -- CODE_SIGNING_ALLOWED=NO
- name: xcodebuild for swift package
id: xcodebuild
run: |
./build-xcframework.sh
- name: Build Xcode project
run: xcodebuild -project examples/llama.swiftui/llama.swiftui.xcodeproj -scheme llama.swiftui -sdk iphoneos CODE_SIGNING_REQUIRED=NO CODE_SIGN_IDENTITY= -destination 'generic/platform=iOS' FRAMEWORK_FOLDER_PATH=./build-ios build
- name: Determine tag name
id: tag
uses: ./.github/actions/get-tag-name
- name: Pack artifacts
id: pack_artifacts
run: |
# Zip file is required for Swift Package Manager, which does not support tar.gz for binary targets.
# For more details, see https://developer.apple.com/documentation/xcode/distributing-binary-frameworks-as-swift-packages
zip -r -y llama-${{ steps.tag.outputs.name }}-xcframework.zip build-apple/llama.xcframework
- name: Upload artifacts
uses: actions/upload-artifact@v6
with:
path: llama-${{ steps.tag.outputs.name }}-xcframework.zip
name: llama-${{ steps.tag.outputs.name }}-xcframework.zip
openEuler-cann:
strategy:
matrix:
include:
# 910b with aclgraph (both architectures)
- arch: x86
chip_type: '910b'
build: 'Release'
use_acl_graph: 'on'
- arch: aarch64
chip_type: '910b'
build: 'Release'
use_acl_graph: 'on'
# 310p without aclgraph (both architectures)
- arch: x86
chip_type: '310p'
build: 'Release'
use_acl_graph: 'off'
- arch: aarch64
chip_type: '310p'
build: 'Release'
use_acl_graph: 'off'
runs-on: ${{ matrix.arch == 'aarch64' && 'ubuntu-24.04-arm' || 'ubuntu-24.04' }}
steps:
- name: Checkout
uses: actions/checkout@v6
with:
fetch-depth: 0
- name: Free up disk space
uses: ggml-org/free-disk-space@v1.3.1
with:
tool-cache: true
- name: Set container image
id: cann-image
run: |
image="ascendai/cann:${{ matrix.chip_type == '910b' && '8.3.rc2-910b-openeuler24.03-py3.11' || '8.3.rc2-310p-openeuler24.03-py3.11' }}"
echo "image=${image}" >> "${GITHUB_OUTPUT}"
- name: Pull container image
run: docker pull "${{ steps.cann-image.outputs.image }}"
- name: Build
env:
BUILD_TYPE: ${{ matrix.build }}
SOC_TYPE: ascend${{ matrix.chip_type }}
USE_ACL_GRAPH: ${{ matrix.use_acl_graph }}
run: |
HOST_UID=$(id -u)
HOST_GID=$(id -g)
docker run --rm \
-v "${PWD}:/workspace" \
-w /workspace \
-e SOC_TYPE=${SOC_TYPE} \
-e BUILD_TYPE=${BUILD_TYPE} \
-e USE_ACL_GRAPH=${USE_ACL_GRAPH} \
"${{ steps.cann-image.outputs.image }}" \
bash -lc '
set -e
yum install -y --setopt=install_weak_deps=False --setopt=tsflags=nodocs git gcc gcc-c++ make cmake openssl-devel
yum clean all && rm -rf /var/cache/yum
git config --global --add safe.directory "/workspace"
export LD_LIBRARY_PATH=${ASCEND_TOOLKIT_HOME}/lib64:${ASCEND_TOOLKIT_HOME}/$(uname -m)-linux/devlib/:${LD_LIBRARY_PATH}
cmake -S . -B build \
-DCMAKE_BUILD_TYPE=${BUILD_TYPE} \
-DGGML_CANN=on \
-DSOC_TYPE=${SOC_TYPE} \
-DUSE_ACL_GRAPH=${USE_ACL_GRAPH}
cmake --build build -j $(nproc)
chown -R '"${HOST_UID}"':'"${HOST_GID}"' /workspace/build
'
- name: Determine tag name
id: tag
uses: ./.github/actions/get-tag-name
- name: Pack artifacts
run: |
cp LICENSE ./build/bin/
tar -czvf llama-${{ steps.tag.outputs.name }}-bin-${{ matrix.chip_type }}-openEuler-${{ matrix.arch }}${{ matrix.use_acl_graph == 'on' && '-aclgraph' || '' }}.tar.gz --transform "s,./,llama-${{ steps.tag.outputs.name }}/," -C ./build/bin .
- name: Upload artifacts
uses: actions/upload-artifact@v6
with:
path: llama-${{ steps.tag.outputs.name }}-bin-${{ matrix.chip_type }}-openEuler-${{ matrix.arch }}${{ matrix.use_acl_graph == 'on' && '-aclgraph' || '' }}.tar.gz
name: llama-bin-${{ matrix.chip_type }}-openEuler-${{ matrix.arch }}${{ matrix.use_acl_graph == 'on' && '-aclgraph' || '' }}.tar.gz
release:
if: ${{ ( github.event_name == 'push' && github.ref == 'refs/heads/master' ) || github.event.inputs.create_release == 'true' }}
# Fine-grant permission
# https://docs.github.com/en/actions/security-for-github-actions/security-guides/automatic-token-authentication#modifying-the-permissions-for-the-github_token
permissions:
contents: write # for creating release
runs-on: ubuntu-latest
needs:
- windows
- windows-cpu
- windows-cuda
- windows-sycl
- windows-hip
- ubuntu-22-cpu
- ubuntu-22-vulkan
- macOS-arm64
- macOS-x64
- ios-xcode-build
- openEuler-cann
steps:
- name: Clone
id: checkout
uses: actions/checkout@v6
with:
fetch-depth: 0
- name: Determine tag name
id: tag
uses: ./.github/actions/get-tag-name
- name: Download artifacts
id: download-artifact
uses: actions/download-artifact@v7
with:
path: ./artifact
merge-multiple: true
- name: Move artifacts
id: move_artifacts
run: |
mkdir -p release
echo "Adding CPU backend files to existing zips..."
for arch in x64 arm64; do
cpu_zip="artifact/llama-bin-win-cpu-${arch}.zip"
temp_dir=$(mktemp -d)
echo "Extracting CPU backend for $arch..."
unzip "$cpu_zip" -d "$temp_dir"
echo "Adding CPU files to $arch zips..."
for target_zip in artifact/llama-bin-win-*-${arch}.zip; do
if [[ "$target_zip" == "$cpu_zip" ]]; then
continue
fi
echo "Adding CPU backend to $(basename "$target_zip")"
realpath_target_zip=$(realpath "$target_zip")
(cd "$temp_dir" && zip -r "$realpath_target_zip" .)
done
rm -rf "$temp_dir"
done
echo "Renaming and moving zips to release..."
for zip_file in artifact/llama-bin-win-*.zip; do
base_name=$(basename "$zip_file" .zip)
zip_name="llama-${{ steps.tag.outputs.name }}-${base_name#llama-}.zip"
echo "Moving $zip_file to release/$zip_name"
mv "$zip_file" "release/$zip_name"
done
echo "Moving other artifacts..."
mv -v artifact/*.zip release
mv -v artifact/*.tar.gz release
- name: Create release
id: create_release
uses: ggml-org/action-create-release@v1
env:
GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
with:
tag_name: ${{ steps.tag.outputs.name }}
body: |
<details open>
${{ github.event.head_commit.message }}
</details>
**macOS/iOS:**
- [macOS Apple Silicon (arm64)](https://github.com/ggml-org/llama.cpp/releases/download/${{ steps.tag.outputs.name }}/llama-${{ steps.tag.outputs.name }}-bin-macos-arm64.tar.gz)
- [macOS Intel (x64)](https://github.com/ggml-org/llama.cpp/releases/download/${{ steps.tag.outputs.name }}/llama-${{ steps.tag.outputs.name }}-bin-macos-x64.tar.gz)
- [iOS XCFramework](https://github.com/ggml-org/llama.cpp/releases/download/${{ steps.tag.outputs.name }}/llama-${{ steps.tag.outputs.name }}-xcframework.zip)
**Linux:**
- [Ubuntu x64 (CPU)](https://github.com/ggml-org/llama.cpp/releases/download/${{ steps.tag.outputs.name }}/llama-${{ steps.tag.outputs.name }}-bin-ubuntu-x64.tar.gz)
- [Ubuntu x64 (Vulkan)](https://github.com/ggml-org/llama.cpp/releases/download/${{ steps.tag.outputs.name }}/llama-${{ steps.tag.outputs.name }}-bin-ubuntu-vulkan-x64.tar.gz)
- [Ubuntu s390x (CPU)](https://github.com/ggml-org/llama.cpp/releases/download/${{ steps.tag.outputs.name }}/llama-${{ steps.tag.outputs.name }}-bin-ubuntu-s390x.tar.gz)
**Windows:**
- [Windows x64 (CPU)](https://github.com/ggml-org/llama.cpp/releases/download/${{ steps.tag.outputs.name }}/llama-${{ steps.tag.outputs.name }}-bin-win-cpu-x64.zip)
- [Windows arm64 (CPU)](https://github.com/ggml-org/llama.cpp/releases/download/${{ steps.tag.outputs.name }}/llama-${{ steps.tag.outputs.name }}-bin-win-cpu-arm64.zip)
- [Windows x64 (CUDA 12)](https://github.com/ggml-org/llama.cpp/releases/download/${{ steps.tag.outputs.name }}/llama-${{ steps.tag.outputs.name }}-bin-win-cuda-12.4-x64.zip) - [CUDA 12.4 DLLs](https://github.com/ggml-org/llama.cpp/releases/download/${{ steps.tag.outputs.name }}/cudart-llama-bin-win-cuda-12.4-x64.zip)
- [Windows x64 (CUDA 13)](https://github.com/ggml-org/llama.cpp/releases/download/${{ steps.tag.outputs.name }}/llama-${{ steps.tag.outputs.name }}-bin-win-cuda-13.1-x64.zip) - [CUDA 13.1 DLLs](https://github.com/ggml-org/llama.cpp/releases/download/${{ steps.tag.outputs.name }}/cudart-llama-bin-win-cuda-13.1-x64.zip)
- [Windows x64 (Vulkan)](https://github.com/ggml-org/llama.cpp/releases/download/${{ steps.tag.outputs.name }}/llama-${{ steps.tag.outputs.name }}-bin-win-vulkan-x64.zip)
- [Windows x64 (SYCL)](https://github.com/ggml-org/llama.cpp/releases/download/${{ steps.tag.outputs.name }}/llama-${{ steps.tag.outputs.name }}-bin-win-sycl-x64.zip)
- [Windows x64 (HIP)](https://github.com/ggml-org/llama.cpp/releases/download/${{ steps.tag.outputs.name }}/llama-${{ steps.tag.outputs.name }}-bin-win-hip-radeon-x64.zip)
**openEuler:**
- [openEuler x86 (310p)](https://github.com/ggml-org/llama.cpp/releases/download/${{ steps.tag.outputs.name }}/llama-${{ steps.tag.outputs.name }}-bin-310p-openEuler-x86.tar.gz)
- [openEuler x86 (910b, ACL Graph)](https://github.com/ggml-org/llama.cpp/releases/download/${{ steps.tag.outputs.name }}/llama-${{ steps.tag.outputs.name }}-bin-910b-openEuler-x86-aclgraph.tar.gz)
- [openEuler aarch64 (310p)](https://github.com/ggml-org/llama.cpp/releases/download/${{ steps.tag.outputs.name }}/llama-${{ steps.tag.outputs.name }}-bin-310p-openEuler-aarch64.tar.gz)
- [openEuler aarch64 (910b, ACL Graph)](https://github.com/ggml-org/llama.cpp/releases/download/${{ steps.tag.outputs.name }}/llama-${{ steps.tag.outputs.name }}-bin-910b-openEuler-aarch64-aclgraph.tar.gz)
- name: Upload release
id: upload_release
uses: actions/github-script@v8
with:
github-token: ${{secrets.GITHUB_TOKEN}}
script: |
const path = require('path');
const fs = require('fs');
const release_id = '${{ steps.create_release.outputs.id }}';
for (let file of await fs.readdirSync('./release')) {
if (path.extname(file) === '.zip' || file.endsWith('.tar.gz')) {
console.log('uploadReleaseAsset', file);
await github.rest.repos.uploadReleaseAsset({
owner: context.repo.owner,
repo: context.repo.repo,
release_id: release_id,
name: file,
data: await fs.readFileSync(`./release/${file}`)
});
}
}

View File

@ -1,219 +0,0 @@
# Server WebUI build and tests
name: Server WebUI
on:
workflow_dispatch: # allows manual triggering
inputs:
sha:
description: 'Commit SHA1 to build'
required: false
type: string
slow_tests:
description: 'Run slow tests'
required: true
type: boolean
push:
branches:
- master
paths: ['.github/workflows/server-webui.yml', 'tools/server/webui/**.*', 'tools/server/tests/**.*', 'tools/server/public/**']
pull_request:
types: [opened, synchronize, reopened]
paths: ['.github/workflows/server-webui.yml', 'tools/server/webui/**.*', 'tools/server/tests/**.*', 'tools/server/public/**']
env:
LLAMA_LOG_COLORS: 1
LLAMA_LOG_PREFIX: 1
LLAMA_LOG_TIMESTAMPS: 1
LLAMA_LOG_VERBOSITY: 10
concurrency:
group: ${{ github.workflow }}-${{ github.ref }}-${{ github.head_ref || github.run_id }}
cancel-in-progress: true
jobs:
webui-check:
name: WebUI Checks
runs-on: ubuntu-latest
continue-on-error: true
steps:
- name: Checkout code
uses: actions/checkout@v6
with:
fetch-depth: 0
ref: ${{ github.event.inputs.sha || github.event.pull_request.head.sha || github.sha || github.head_ref || github.ref_name }}
- name: Setup Node.js
id: node
uses: actions/setup-node@v6
with:
node-version: "22"
cache: "npm"
cache-dependency-path: "tools/server/webui/package-lock.json"
- name: Install dependencies
id: setup
if: ${{ steps.node.conclusion == 'success' }}
run: npm ci
working-directory: tools/server/webui
- name: Run type checking
if: ${{ always() && steps.setup.conclusion == 'success' }}
run: npm run check
working-directory: tools/server/webui
- name: Run linting
if: ${{ always() && steps.setup.conclusion == 'success' }}
run: npm run lint
working-directory: tools/server/webui
- name: Build application
if: ${{ always() && steps.setup.conclusion == 'success' }}
run: npm run build
working-directory: tools/server/webui
- name: Install Playwright browsers
id: playwright
if: ${{ always() && steps.setup.conclusion == 'success' }}
run: npx playwright install --with-deps
working-directory: tools/server/webui
- name: Build Storybook
if: ${{ always() && steps.playwright.conclusion == 'success' }}
run: npm run build-storybook
working-directory: tools/server/webui
- name: Run Client tests
if: ${{ always() && steps.playwright.conclusion == 'success' }}
run: npm run test:client
working-directory: tools/server/webui
- name: Run Unit tests
if: ${{ always() && steps.playwright.conclusion == 'success' }}
run: npm run test:unit
working-directory: tools/server/webui
- name: Run UI tests
if: ${{ always() && steps.playwright.conclusion == 'success' }}
run: npm run test:ui -- --testTimeout=60000
working-directory: tools/server/webui
- name: Run E2E tests
if: ${{ always() && steps.playwright.conclusion == 'success' }}
run: npm run test:e2e
working-directory: tools/server/webui
server-build:
runs-on: ubuntu-latest
strategy:
matrix:
sanitizer: [ADDRESS, UNDEFINED] # THREAD is broken
build_type: [RelWithDebInfo]
include:
- build_type: Release
sanitizer: ""
fail-fast: false # While -DLLAMA_SANITIZE_THREAD=ON is broken
steps:
- name: Dependencies
id: depends
run: |
sudo apt-get update
sudo apt-get -y install \
build-essential \
xxd \
git \
cmake \
curl \
wget \
language-pack-en \
libssl-dev
- name: Clone
id: checkout
uses: actions/checkout@v6
with:
fetch-depth: 0
ref: ${{ github.event.inputs.sha || github.event.pull_request.head.sha || github.sha || github.head_ref || github.ref_name }}
- name: Python setup
id: setup_python
uses: actions/setup-python@v6
with:
python-version: '3.11'
- name: Tests dependencies
id: test_dependencies
run: |
pip install -r tools/server/tests/requirements.txt
- name: Setup Node.js for WebUI
uses: actions/setup-node@v6
with:
node-version: "22"
cache: "npm"
cache-dependency-path: "tools/server/webui/package-lock.json"
- name: Install WebUI dependencies
run: npm ci
working-directory: tools/server/webui
- name: Build WebUI
run: npm run build
working-directory: tools/server/webui
- name: Build (no OpenMP)
id: cmake_build_no_openmp
if: ${{ matrix.sanitizer == 'THREAD' }}
run: |
cmake -B build \
-DGGML_NATIVE=OFF \
-DLLAMA_BUILD_SERVER=ON \
-DCMAKE_BUILD_TYPE=${{ matrix.build_type }} \
-DLLAMA_SANITIZE_${{ matrix.sanitizer }}=ON \
-DGGML_OPENMP=OFF ;
cmake --build build --config ${{ matrix.build_type }} -j $(nproc) --target llama-server
- name: Build (sanitizers)
id: cmake_build_sanitizers
if: ${{ matrix.sanitizer != '' && matrix.sanitizer != 'THREAD' }}
run: |
cmake -B build \
-DGGML_NATIVE=OFF \
-DLLAMA_BUILD_SERVER=ON \
-DCMAKE_BUILD_TYPE=${{ matrix.build_type }} \
-DLLAMA_SANITIZE_${{ matrix.sanitizer }}=ON ;
cmake --build build --config ${{ matrix.build_type }} -j $(nproc) --target llama-server
- name: Build (sanitizers)
id: cmake_build
if: ${{ matrix.sanitizer == '' }}
run: |
cmake -B build \
-DGGML_NATIVE=OFF \
-DLLAMA_BUILD_SERVER=ON \
-DCMAKE_BUILD_TYPE=${{ matrix.build_type }} ;
cmake --build build --config ${{ matrix.build_type }} -j $(nproc) --target llama-server
- name: Tests
id: server_integration_tests
if: ${{ matrix.sanitizer == '' }}
env:
GITHUB_ACTIONS: "true"
run: |
cd tools/server/tests
./tests.sh
- name: Tests (sanitizers)
id: server_integration_tests_sanitizers
if: ${{ matrix.sanitizer != '' }}
run: |
cd tools/server/tests
LLAMA_SANITIZE=1 ./tests.sh
- name: Slow tests
id: server_integration_tests_slow
if: ${{ (github.event.schedule || github.event.inputs.slow_tests == 'true') && matrix.build_type == 'Release' }}
run: |
cd tools/server/tests
SLOW_TESTS=1 ./tests.sh

View File

@ -15,10 +15,10 @@ on:
push:
branches:
- master
paths: ['.github/workflows/server.yml', '**/CMakeLists.txt', '**/Makefile', '**/*.h', '**/*.hpp', '**/*.c', '**/*.cpp', '**/*.cu', '**/*.swift', '**/*.m', 'tools/server/**.*']
paths: ['.github/workflows/server.yml', '**/CMakeLists.txt', '**/Makefile', '**/*.h', '**/*.hpp', '**/*.c', '**/*.cpp', '**/*.cu', '**/*.swift', '**/*.m', 'examples/server/**.*']
pull_request:
types: [opened, synchronize, reopened]
paths: ['.github/workflows/server.yml', '**/CMakeLists.txt', '**/Makefile', '**/*.h', '**/*.hpp', '**/*.c', '**/*.cpp', '**/*.cu', '**/*.swift', '**/*.m', 'tools/server/**.*']
paths: ['.github/workflows/server.yml', '**/CMakeLists.txt', '**/Makefile', '**/*.h', '**/*.hpp', '**/*.c', '**/*.cpp', '**/*.cu', '**/*.swift', '**/*.m', 'examples/server/**.*']
env:
LLAMA_LOG_COLORS: 1
@ -36,16 +36,12 @@ jobs:
strategy:
matrix:
sanitizer: [ADDRESS, UNDEFINED] # THREAD is very slow
sanitizer: [ADDRESS, UNDEFINED] # THREAD is broken
build_type: [RelWithDebInfo]
include:
- build_type: Release
sanitizer: ""
extra_args: ""
- build_type: Release
sanitizer: ""
extra_args: "LLAMA_ARG_BACKEND_SAMPLING=1"
fail-fast: false
fail-fast: false # While -DLLAMA_SANITIZE_THREAD=ON is broken
steps:
- name: Dependencies
@ -60,81 +56,175 @@ jobs:
curl \
wget \
language-pack-en \
libssl-dev
libcurl4-openssl-dev
- name: Clone
id: checkout
uses: actions/checkout@v6
uses: actions/checkout@v4
with:
fetch-depth: 0
ref: ${{ github.event.inputs.sha || github.event.pull_request.head.sha || github.sha || github.head_ref || github.ref_name }}
- name: Build
id: cmake_build
run: |
cmake -B build \
-DLLAMA_BUILD_BORINGSSL=ON \
-DGGML_SCHED_NO_REALLOC=ON \
-DGGML_SANITIZE_ADDRESS=${{ matrix.sanitizer == 'ADDRESS' }} \
-DGGML_SANITIZE_THREAD=${{ matrix.sanitizer == 'THREAD' }} \
-DGGML_SANITIZE_UNDEFINED=${{ matrix.sanitizer == 'UNDEFINED' }} \
-DLLAMA_SANITIZE_ADDRESS=${{ matrix.sanitizer == 'ADDRESS' }} \
-DLLAMA_SANITIZE_THREAD=${{ matrix.sanitizer == 'THREAD' }} \
-DLLAMA_SANITIZE_UNDEFINED=${{ matrix.sanitizer == 'UNDEFINED' }}
cmake --build build --config ${{ matrix.build_type }} -j ${env:NUMBER_OF_PROCESSORS} --target llama-server
- name: Python setup
id: setup_python
uses: actions/setup-python@v6
uses: actions/setup-python@v5
with:
python-version: '3.11'
- name: Tests dependencies
id: test_dependencies
run: |
pip install -r tools/server/tests/requirements.txt
pip install -r examples/server/tests/requirements.txt
# Setup nodejs (to be used for verifying bundled index.html)
- uses: actions/setup-node@v4
with:
node-version: '22.11.0'
- name: WebUI - Install dependencies
id: webui_lint
run: |
cd examples/server/webui
npm ci
- name: WebUI - Check code format
id: webui_format
run: |
git config --global --add safe.directory $(realpath .)
cd examples/server/webui
git status
npm run format
git status
modified_files="$(git status -s)"
echo "Modified files: ${modified_files}"
if [ -n "${modified_files}" ]; then
echo "Files do not follow coding style. To fix: npm run format"
echo "${modified_files}"
exit 1
fi
- name: Verify bundled index.html
id: verify_server_index_html
run: |
git config --global --add safe.directory $(realpath .)
cd examples/server/webui
git status
npm run build
git status
modified_files="$(git status -s)"
echo "Modified files: ${modified_files}"
if [ -n "${modified_files}" ]; then
echo "Repository is dirty or server/webui is not built as expected"
echo "Hint: You may need to follow Web UI build guide in server/README.md"
echo "${modified_files}"
exit 1
fi
- name: Build (no OpenMP)
id: cmake_build_no_openmp
if: ${{ matrix.sanitizer == 'THREAD' }}
run: |
cmake -B build \
-DGGML_NATIVE=OFF \
-DLLAMA_BUILD_SERVER=ON \
-DCMAKE_BUILD_TYPE=${{ matrix.build_type }} \
-DLLAMA_SANITIZE_${{ matrix.sanitizer }}=ON \
-DGGML_OPENMP=OFF ;
cmake --build build --config ${{ matrix.build_type }} -j $(nproc) --target llama-server
- name: Build (sanitizers)
id: cmake_build_sanitizers
if: ${{ matrix.sanitizer != '' && matrix.sanitizer != 'THREAD' }}
run: |
cmake -B build \
-DGGML_NATIVE=OFF \
-DLLAMA_BUILD_SERVER=ON \
-DCMAKE_BUILD_TYPE=${{ matrix.build_type }} \
-DLLAMA_SANITIZE_${{ matrix.sanitizer }}=ON ;
cmake --build build --config ${{ matrix.build_type }} -j $(nproc) --target llama-server
- name: Build (sanitizers)
id: cmake_build
if: ${{ matrix.sanitizer == '' }}
run: |
cmake -B build \
-DGGML_NATIVE=OFF \
-DLLAMA_BUILD_SERVER=ON \
-DCMAKE_BUILD_TYPE=${{ matrix.build_type }} ;
cmake --build build --config ${{ matrix.build_type }} -j $(nproc) --target llama-server
- name: Tests
id: server_integration_tests
if: ${{ (!matrix.disabled_on_pr || !github.event.pull_request) }}
if: ${{ matrix.sanitizer == '' }}
env:
GITHUB_ACTIONS: "true"
run: |
cd tools/server/tests
export ${{ matrix.extra_args }}
pytest -v -x -m "not slow"
cd examples/server/tests
./tests.sh
- name: Tests (sanitizers)
id: server_integration_tests_sanitizers
if: ${{ matrix.sanitizer != '' }}
run: |
cd examples/server/tests
LLAMA_SANITIZE=1 ./tests.sh
- name: Slow tests
id: server_integration_tests_slow
if: ${{ (github.event.schedule || github.event.inputs.slow_tests == 'true') && matrix.build_type == 'Release' }}
run: |
cd examples/server/tests
SLOW_TESTS=1 ./tests.sh
server-windows:
runs-on: windows-2022
runs-on: windows-2019
steps:
- name: Clone
id: checkout
uses: actions/checkout@v6
uses: actions/checkout@v4
with:
fetch-depth: 0
ref: ${{ github.event.inputs.sha || github.event.pull_request.head.sha || github.sha || github.head_ref || github.ref_name }}
- name: libCURL
id: get_libcurl
uses: ./.github/actions/windows-setup-curl
- name: Build
id: cmake_build
env:
CURL_PATH: ${{ steps.get_libcurl.outputs.curl_path }}
run: |
cmake -B build -DLLAMA_BUILD_BORINGSSL=ON -DGGML_SCHED_NO_REALLOC=ON
cmake -B build -DCURL_LIBRARY="$env:CURL_PATH/lib/libcurl.dll.a" -DCURL_INCLUDE_DIR="$env:CURL_PATH/include"
cmake --build build --config Release -j ${env:NUMBER_OF_PROCESSORS} --target llama-server
- name: Python setup
id: setup_python
uses: actions/setup-python@v6
uses: actions/setup-python@v5
with:
python-version: '3.11'
- name: Tests dependencies
id: test_dependencies
run: |
pip install -r tools/server/tests/requirements.txt
pip install -r examples/server/tests/requirements.txt
- name: Copy Libcurl
id: prepare_libcurl
env:
CURL_PATH: ${{ steps.get_libcurl.outputs.curl_path }}
run: |
cp $env:CURL_PATH/bin/libcurl-x64.dll ./build/bin/Release/libcurl-x64.dll
- name: Tests
id: server_integration_tests
if: ${{ !matrix.disabled_on_pr || !github.event.pull_request }}
run: |
cd tools/server/tests
cd examples/server/tests
$env:PYTHONIOENCODING = ":replace"
pytest -v -x -m "not slow"
@ -142,6 +232,6 @@ jobs:
id: server_integration_tests_slow
if: ${{ (github.event.schedule || github.event.inputs.slow_tests == 'true') && matrix.build_type == 'Release' }}
run: |
cd tools/server/tests
cd examples/server/tests
$env:SLOW_TESTS = "1"
pytest -v -x

View File

@ -1,42 +0,0 @@
name: Update Operations Documentation
on:
push:
paths:
- 'docs/ops.md'
- 'docs/ops/**'
- 'scripts/create_ops_docs.py'
pull_request:
paths:
- 'docs/ops.md'
- 'docs/ops/**'
- 'scripts/create_ops_docs.py'
jobs:
update-ops-docs:
runs-on: ubuntu-slim
steps:
- name: Checkout repository
uses: actions/checkout@v6
- name: Set up Python
uses: actions/setup-python@v6
with:
python-version: '3.x'
- name: Generate operations documentation to temporary file
run: |
mkdir -p /tmp/ops_check
./scripts/create_ops_docs.py /tmp/ops_check/ops.md
- name: Check if docs/ops.md matches generated version
run: |
if ! diff -q docs/ops.md /tmp/ops_check/ops.md; then
echo "Operations documentation (docs/ops.md) is not up to date with the backend CSV files."
echo "To fix: run ./scripts/create_ops_docs.py and commit the updated docs/ops.md along with your changes"
echo "Differences found:"
diff docs/ops.md /tmp/ops_check/ops.md || true
exit 1
fi
echo "Operations documentation is up to date."

View File

@ -1,44 +0,0 @@
name: Update Winget Package
on:
workflow_dispatch: # allows manual triggering
schedule:
- cron: '28 5 * * *' # Update every day at 5:28 UTC
jobs:
update:
name: Update Winget Package
runs-on: ubuntu-latest
if: github.repository_owner == 'ggml-org'
steps:
- name: Install cargo binstall
uses: cargo-bins/cargo-binstall@268643a6b5ea099f5718ee5cd3ff7dc89a5eb49b
- name: Install komac
run: |
cargo binstall komac@2.11.2 -y
- name: Find latest release
id: find_latest_release
uses: actions/github-script@v8
with:
script: |
const { data: releases } = await github.rest.repos.listReleases({
owner: context.repo.owner,
repo: context.repo.repo,
});
const { tag_name: version, assets: assets } = releases.find(({assets}) => assets.find(asset => asset.name.includes('win-vulkan')));
const { browser_download_url: asset_url } = assets.find(asset => asset.name.includes('win-vulkan'));
console.log("Latest release:", version);
core.setOutput('VERSION', version);
core.setOutput('ASSETURL', asset_url);
- name: Update manifest
run: |
echo "Updating manifest..."
komac update --version ${{ steps.find_latest_release.outputs.VERSION }} \
--urls "${{ steps.find_latest_release.outputs.ASSETURL }}" \
--token ${{ secrets.WINGET_GITHUB_TOKEN }} \
--submit \
ggml.llamacpp

110
.gitignore vendored
View File

@ -20,41 +20,52 @@
*.so
*.swp
*.tmp
*.DS_Store
# IDE / OS
/.cache/
/.ccls-cache/
/.direnv/
/.envrc
/.idea/
/.swiftpm
/.vs/
/.vscode/
/nppBackup
.cache/
.ccls-cache/
.direnv/
.DS_Store
.envrc
.idea/
.swiftpm
.vs/
.vscode/
nppBackup
# Coverage
/gcovr-report/
/lcov-report/
gcovr-report/
lcov-report/
# Build Artifacts
/tags
/.build/
/build*
/release
/debug
tags
.build/
build*
release
debug
!build-info.cmake
!build-info.cpp.in
!build-info.sh
!build.zig
!docs/build.md
/libllama.so
/llama-*
/vulkan-shaders-gen
android-ndk-*
arm_neon.h
cmake-build-*
CMakeSettings.json
compile_commands.json
ggml-metal-embed.metal
llama-batched-swift
/rpc-server
/out/
/tmp/
/autogen-*.md
/common/build-info.cpp
out/
tmp/
autogen-*.md
# Deprecated
@ -63,38 +74,43 @@
# CI
!/.github/workflows/*.yml
!.github/workflows/*.yml
# Models
/models/*
/models-mnt
!/models/.editorconfig
!/models/ggml-vocab-*.gguf*
!/models/templates
models/*
models-mnt
!models/.editorconfig
!models/ggml-vocab-*.gguf*
# Zig
/zig-out/
/zig-cache/
zig-out/
zig-cache/
# Logs
ppl-*.txt
qnt-*.txt
perf-*.txt
# Examples
/examples/jeopardy/results.txt
/tools/server/*.css.hpp
/tools/server/*.html.hpp
/tools/server/*.js.hpp
/tools/server/*.mjs.hpp
/tools/server/*.gz.hpp
!/build_64.sh
!/examples/*.bat
!/examples/*/*.kts
!/examples/*/*/*.kts
!/examples/sycl/*.bat
!/examples/sycl/*.sh
examples/jeopardy/results.txt
examples/server/*.css.hpp
examples/server/*.html.hpp
examples/server/*.js.hpp
examples/server/*.mjs.hpp
examples/server/*.gz.hpp
!build_64.sh
!examples/*.bat
!examples/*/*.kts
!examples/*/*/*.kts
!examples/sycl/*.bat
!examples/sycl/*.sh
# Server Web UI temporary files
/tools/server/webui/node_modules
/tools/server/webui/dist
node_modules
examples/server/webui/dist
# Python
@ -130,11 +146,3 @@ poetry.toml
# Local scripts
/run-vim.sh
/run-chat.sh
/run-spec.sh
/.ccache/
# IDE
/*.code-workspace
/.windsurf/
# emscripten
a.out.*

3
.gitmodules vendored
View File

@ -0,0 +1,3 @@
[submodule "kompute"]
path = ggml/src/ggml-kompute/kompute
url = https://github.com/nomic-ai/kompute.git

View File

@ -1,81 +0,0 @@
# Instructions for llama.cpp
> [!IMPORTANT]
> This project does **not** accept pull requests that are fully or predominantly AI-generated. AI tools may be utilized solely in an assistive capacity.
>
> Read more: [CONTRIBUTING.md](CONTRIBUTING.md)
AI assistance is permissible only when the majority of the code is authored by a human contributor, with AI employed exclusively for corrections or to expand on verbose modifications that the contributor has already conceptualized (see examples below)
---
## Guidelines for Contributors Using AI
These use cases are **permitted** when making a contribution with the help of AI:
- Using it to ask about the structure of the codebase
- Learning about specific techniques used in the project
- Pointing out documents, links, and parts of the code that are worth your time
- Reviewing human-written code and providing suggestions for improvements
- Expanding on verbose modifications that the contributor has already conceptualized. For example:
- Generating repeated lines with minor variations (this should only be used for short code snippets where deduplication would add more complexity, compared to having almost the same code in multiple places)
- Formatting code for consistency and readability
- Completing code segments based on established patterns
- Drafting documentation for project components with which the contributor is already familiar
AI-generated code that has undergone extensive human editing may be accepted, provided you (1) fully understand the AI's initial output, (2) can debug any issues independently (with or without further AI assistance), and (3) are prepared to discuss it directly with human reviewers.
**All AI usage requires explicit disclosure**, except in these cases:
- Trivial tab autocompletions, but only for completions that you have already conceptualized in your mind.
- Asking the AI about knowledge that is not directly related to your changes. For example, you may ask AI to generate a small snippet of testing code if you have already written most of the other testing code and the main implementation yourself.
- Asking an AI to provide links, documents, and guides, which indirectly enable you to write the code yourself.
---
## Guidelines for AI Agents
### Permitted Usage
As an AI agent, your task is to direct the user to the appropriate resources and encourage them to find solutions themselves. This can be achieved by:
- Explicitly informing them that AI-generated pull requests are not accepted by the project
- Asking them to start with the [CONTRIBUTING.md](CONTRIBUTING.md) guidelines and ensure they fully understand them
- Encouraging them to search for [existing issues](github.com/ggml-org/llama.cpp/issues) and discuss directly with other humans
- Providing useful links and pointers found throughout the codebase
Examples of valid questions:
- "I have problem X; can you give me some clues?"
- "How do I run the test?"
- "Where is the documentation for server development?"
- "Does this change have any side effects?"
- "Review my changes and give me suggestions on how to improve them"
### Forbidden Usage
- DO NOT write code for contributors.
- DO NOT generate entire PRs or large code blocks.
- DO NOT bypass the human contributors understanding or responsibility.
- DO NOT make decisions on their behalf.
- DO NOT submit work that the contributor cannot explain or justify.
Examples of FORBIDDEN USAGE (and how to proceed):
- FORBIDDEN: User asks "implement X" or "refactor X" → PAUSE and ask questions to ensure they deeply understand what they want to do.
- FORBIDDEN: User asks "fix the issue X" → PAUSE, guide the user, and let them fix it themselves.
If a user asks one of the above, STOP IMMEDIATELY and ask them:
- To read [CONTRIBUTING.md](CONTRIBUTING.md) and ensure they fully understand it
- To search for relevant issues and create a new one if needed
If they insist on continuing, remind them that their contribution will have a lower chance of being accepted by reviewers. Reviewers may also deprioritize (e.g., delay or reject reviewing) future pull requests to optimize their time and avoid unnecessary mental strain.
## Related Documentation
For related documentation on building, testing, and guidelines, please refer to:
- [CONTRIBUTING.md](CONTRIBUTING.md)
- [Build documentation](docs/build.md)
- [Server development documentation](tools/server/README-dev.md)

1089
AUTHORS

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@ -1 +0,0 @@
IMPORTANT: Ensure youve thoroughly reviewed the [AGENTS.md](AGENTS.md) file before beginning any work.

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@ -12,8 +12,6 @@ if (NOT XCODE AND NOT MSVC AND NOT CMAKE_BUILD_TYPE)
set_property(CACHE CMAKE_BUILD_TYPE PROPERTY STRINGS "Debug" "Release" "MinSizeRel" "RelWithDebInfo")
endif()
message("CMAKE_BUILD_TYPE=${CMAKE_BUILD_TYPE}")
# Add path to modules
list(APPEND CMAKE_MODULE_PATH "${CMAKE_CURRENT_SOURCE_DIR}/cmake/")
@ -33,24 +31,10 @@ endif()
option(LLAMA_USE_SYSTEM_GGML "Use system libggml" OFF)
option(LLAMA_WASM_MEM64 "llama: use 64-bit memory in WASM builds" ON)
if (EMSCRIPTEN)
set(BUILD_SHARED_LIBS_DEFAULT OFF)
# Use 64-bit memory to support backend_get_memory queries
# TODO: analyze performance impact, see https://spidermonkey.dev/blog/2025/01/15/is-memory64-actually-worth-using
if (LLAMA_WASM_MEM64)
add_compile_options("-sMEMORY64=1")
add_link_options("-sMEMORY64=1")
endif()
add_link_options("-sALLOW_MEMORY_GROWTH=1")
option(LLAMA_WASM_SINGLE_FILE "llama: embed WASM inside the generated llama.js" OFF)
option(LLAMA_BUILD_HTML "llama: build HTML file" ON)
if (LLAMA_BUILD_HTML)
set(CMAKE_EXECUTABLE_SUFFIX ".html")
endif()
option(LLAMA_WASM_SINGLE_FILE "llama: embed WASM inside the generated llama.js" ON)
else()
if (MINGW)
set(BUILD_SHARED_LIBS_DEFAULT OFF)
@ -72,18 +56,6 @@ if (MSVC)
add_compile_options("$<$<COMPILE_LANGUAGE:CXX>:/bigobj>")
endif()
if (LLAMA_STANDALONE)
# enable parallel builds for msbuild
list(APPEND CMAKE_VS_GLOBALS UseMultiToolTask=true)
list(APPEND CMAKE_VS_GLOBALS EnforceProcessCountAcrossBuilds=true)
endif()
if (CMAKE_SYSTEM_NAME STREQUAL "iOS")
set(LLAMA_TOOLS_INSTALL_DEFAULT OFF)
else()
set(LLAMA_TOOLS_INSTALL_DEFAULT ${LLAMA_STANDALONE})
endif()
#
# option list
#
@ -105,34 +77,17 @@ option(LLAMA_BUILD_COMMON "llama: build common utils library" ${LLAMA_STANDALONE
# extra artifacts
option(LLAMA_BUILD_TESTS "llama: build tests" ${LLAMA_STANDALONE})
option(LLAMA_BUILD_TOOLS "llama: build tools" ${LLAMA_STANDALONE})
option(LLAMA_BUILD_EXAMPLES "llama: build examples" ${LLAMA_STANDALONE})
option(LLAMA_BUILD_SERVER "llama: build server example" ${LLAMA_STANDALONE})
option(LLAMA_TOOLS_INSTALL "llama: install tools" ${LLAMA_TOOLS_INSTALL_DEFAULT})
# 3rd party libs
option(LLAMA_HTTPLIB "llama: httplib for downloading functionality" ON)
option(LLAMA_OPENSSL "llama: use openssl to support HTTPS" ON)
option(LLAMA_CURL "llama: use libcurl to download model from an URL" ON)
option(LLAMA_LLGUIDANCE "llama-common: include LLGuidance library for structured output in common utils" OFF)
# deprecated
option(LLAMA_CURL "llama: use libcurl to download model from an URL" OFF)
if (LLAMA_CURL)
message(WARNING "LLAMA_CURL option is deprecated and will be ignored")
endif()
# Required for relocatable CMake package
include(${CMAKE_CURRENT_SOURCE_DIR}/cmake/build-info.cmake)
include(${CMAKE_CURRENT_SOURCE_DIR}/cmake/common.cmake)
if (NOT DEFINED LLAMA_BUILD_NUMBER)
set(LLAMA_BUILD_NUMBER ${BUILD_NUMBER})
endif()
if (NOT DEFINED LLAMA_BUILD_COMMIT)
set(LLAMA_BUILD_COMMIT ${BUILD_COMMIT})
endif()
set(LLAMA_INSTALL_VERSION 0.0.${LLAMA_BUILD_NUMBER})
# override ggml options
set(GGML_ALL_WARNINGS ${LLAMA_ALL_WARNINGS})
set(GGML_FATAL_WARNINGS ${LLAMA_FATAL_WARNINGS})
@ -156,6 +111,7 @@ endfunction()
llama_option_depr(FATAL_ERROR LLAMA_CUBLAS GGML_CUDA)
llama_option_depr(WARNING LLAMA_CUDA GGML_CUDA)
llama_option_depr(WARNING LLAMA_KOMPUTE GGML_KOMPUTE)
llama_option_depr(WARNING LLAMA_METAL GGML_METAL)
llama_option_depr(WARNING LLAMA_METAL_EMBED_LIBRARY GGML_METAL_EMBED_LIBRARY)
llama_option_depr(WARNING LLAMA_NATIVE GGML_NATIVE)
@ -164,8 +120,28 @@ llama_option_depr(WARNING LLAMA_SYCL GGML_SYCL)
llama_option_depr(WARNING LLAMA_SYCL_F16 GGML_SYCL_F16)
llama_option_depr(WARNING LLAMA_CANN GGML_CANN)
include("cmake/license.cmake")
license_add_file("llama.cpp" "LICENSE")
if (NOT MSVC)
if (LLAMA_SANITIZE_THREAD)
message(STATUS "Using -fsanitize=thread")
add_compile_options(-fsanitize=thread)
link_libraries (-fsanitize=thread)
endif()
if (LLAMA_SANITIZE_ADDRESS)
message(STATUS "Using -fsanitize=address")
add_compile_options(-fsanitize=address -fno-omit-frame-pointer)
link_libraries (-fsanitize=address)
endif()
if (LLAMA_SANITIZE_UNDEFINED)
message(STATUS "Using -fsanitize=undefined")
add_compile_options(-fsanitize=undefined)
link_libraries (-fsanitize=undefined)
endif()
endif()
#
# 3rd-party
@ -178,8 +154,6 @@ if (LLAMA_USE_SYSTEM_GGML)
endif()
if (NOT TARGET ggml AND NOT LLAMA_USE_SYSTEM_GGML)
set(GGML_BUILD_NUMBER ${LLAMA_BUILD_NUMBER})
set(GGML_BUILD_COMMIT ${LLAMA_BUILD_COMMIT})
add_subdirectory(ggml)
# ... otherwise assume ggml is added by a parent CMakeLists.txt
endif()
@ -194,11 +168,13 @@ add_subdirectory(src)
# utils, programs, examples and tests
#
if (NOT LLAMA_BUILD_COMMON)
message(STATUS "LLAMA_BUILD_COMMON is OFF, disabling LLAMA_CURL")
set(LLAMA_CURL OFF)
endif()
if (LLAMA_BUILD_COMMON)
add_subdirectory(common)
if (LLAMA_HTTPLIB)
add_subdirectory(vendor/cpp-httplib)
endif()
endif()
if (LLAMA_BUILD_COMMON AND LLAMA_BUILD_TESTS AND NOT CMAKE_JS_VERSION)
@ -211,23 +187,6 @@ if (LLAMA_BUILD_COMMON AND LLAMA_BUILD_EXAMPLES)
add_subdirectory(pocs)
endif()
if (LLAMA_BUILD_COMMON AND LLAMA_BUILD_TOOLS)
add_subdirectory(tools)
endif()
# Automatically add all files from the 'licenses' directory
file(GLOB EXTRA_LICENSES "${CMAKE_SOURCE_DIR}/licenses/LICENSE-*")
foreach(FILE_PATH ${EXTRA_LICENSES})
get_filename_component(FILE_NAME "${FILE_PATH}" NAME)
string(REGEX REPLACE "^LICENSE-" "" NAME "${FILE_NAME}")
license_add_file("${NAME}" "${FILE_PATH}")
endforeach()
if (LLAMA_BUILD_COMMON)
license_generate(common)
endif()
#
# install
#
@ -235,6 +194,10 @@ endif()
include(GNUInstallDirs)
include(CMakePackageConfigHelpers)
set(LLAMA_BUILD_NUMBER ${BUILD_NUMBER})
set(LLAMA_BUILD_COMMIT ${BUILD_COMMIT})
set(LLAMA_INSTALL_VERSION 0.0.${BUILD_NUMBER})
set(LLAMA_INCLUDE_INSTALL_DIR ${CMAKE_INSTALL_INCLUDEDIR} CACHE PATH "Location of header files")
set(LLAMA_LIB_INSTALL_DIR ${CMAKE_INSTALL_LIBDIR} CACHE PATH "Location of library files")
set(LLAMA_BIN_INSTALL_DIR ${CMAKE_INSTALL_BINDIR} CACHE PATH "Location of binary files")
@ -284,3 +247,20 @@ configure_file(cmake/llama.pc.in
install(FILES "${CMAKE_CURRENT_BINARY_DIR}/llama.pc"
DESTINATION ${CMAKE_INSTALL_LIBDIR}/pkgconfig)
#
# copy the license files
#
# Check if running in GitHub Actions
if(DEFINED ENV{GITHUB_ACTIONS} AND "$ENV{GITHUB_ACTIONS}" STREQUAL "true")
message(STATUS "Running inside GitHub Actions - copying license files")
# Copy all files from licenses/ to build/bin/
file(GLOB LICENSE_FILES "${CMAKE_SOURCE_DIR}/licenses/*")
foreach(LICENSE_FILE ${LICENSE_FILES})
get_filename_component(FILENAME ${LICENSE_FILE} NAME)
configure_file(${LICENSE_FILE} "${CMAKE_BINARY_DIR}/bin/${FILENAME}" COPYONLY)
endforeach()
endif()

View File

@ -38,6 +38,15 @@
}
},
{
"name": "arm64-windows-msvc", "hidden": true,
"architecture": { "value": "arm64", "strategy": "external" },
"toolset": { "value": "host=x64", "strategy": "external" },
"cacheVariables": {
"CMAKE_TOOLCHAIN_FILE": "${sourceDir}/cmake/arm64-windows-msvc.cmake"
}
},
{
"name": "arm64-windows-llvm", "hidden": true,
"architecture": { "value": "arm64", "strategy": "external" },
@ -55,17 +64,6 @@
"CMAKE_TOOLCHAIN_FILE": "${sourceDir}/cmake/arm64-apple-clang.cmake"
}
},
{
"name": "x64-linux-gcc", "hidden": true,
"cacheVariables": {
"CMAKE_C_COMPILER": "gcc",
"CMAKE_CXX_COMPILER": "g++"
}
},
{ "name": "x64-linux-gcc-debug", "inherits": [ "base", "x64-linux-gcc", "debug" ] },
{ "name": "x64-linux-gcc-release", "inherits": [ "base", "x64-linux-gcc", "release" ] },
{ "name": "x64-linux-gcc-reldbg", "inherits": [ "base", "x64-linux-gcc", "reldbg" ] },
{ "name": "x64-linux-gcc+static-release", "inherits": [ "base", "x64-linux-gcc", "release", "static" ] },
{ "name": "arm64-windows-llvm-debug", "inherits": [ "base", "arm64-windows-llvm", "debug" ] },
{ "name": "arm64-windows-llvm-release", "inherits": [ "base", "arm64-windows-llvm", "reldbg" ] },
@ -75,6 +73,10 @@
{ "name": "arm64-apple-clang-release", "inherits": [ "base", "arm64-apple-clang", "reldbg" ] },
{ "name": "arm64-apple-clang+static-release", "inherits": [ "base", "arm64-apple-clang", "reldbg", "static" ] },
{ "name": "arm64-windows-msvc-debug", "inherits": [ "base", "arm64-windows-msvc", "debug" ] },
{ "name": "arm64-windows-msvc-release", "inherits": [ "base", "arm64-windows-msvc", "reldbg" ] },
{ "name": "arm64-windows-msvc+static-release", "inherits": [ "base", "arm64-windows-msvc", "reldbg", "static" ] },
{ "name": "x64-windows-llvm-debug", "inherits": [ "base", "x64-windows-llvm", "debug" ] },
{ "name": "x64-windows-llvm-release", "inherits": [ "base", "x64-windows-llvm", "release" ] },
{ "name": "x64-windows-llvm-reldbg", "inherits": [ "base", "x64-windows-llvm", "reldbg" ] },

View File

@ -1,112 +1,11 @@
# collaborators can optionally add themselves here to indicate their availability for reviewing related PRs
# multiplie collaborators per item can be specified
/.devops/*.Dockerfile @ngxson
/.github/actions/ @CISC
/.github/workflows/ @CISC
/ci/ @ggerganov
/cmake/ @ggerganov
/common/CMakeLists.txt @ggerganov
/common/arg.* @ggerganov
/common/base64.hpp.* @ggerganov
/common/build-info.* @ggerganov
/common/chat.* @pwilkin
/common/chat-peg-parser.* @aldehir
/common/common.* @ggerganov
/common/console.* @ggerganov
/common/http.* @angt
/common/jinja/ @ngxson @CISC @aldehir
/common/llguidance.* @ggerganov
/common/log.* @ggerganov
/common/ngram-map.* @srogmann
/common/peg-parser.* @aldehir
/common/sampling.* @ggerganov
/common/speculative.* @ggerganov
/common/unicode.* @aldehir
/convert_*.py @CISC
/examples/batched.swift/ @ggerganov
/examples/batched/ @ggerganov
/examples/convert-llama2c-to-ggml/ @ggerganov
/examples/debug/ @danbev @pwilkin
/examples/deprecation-warning/ @ggerganov
/examples/diffusion/ @am17an
/examples/embedding/ @ggerganov
/examples/eval-callback/ @ggerganov
/examples/export-docs/ @ggerganov
/examples/gen-docs/ @ggerganov
/examples/gguf/ @ggerganov
/examples/llama.android/ @ggerganov @hanyin-arm @naco-siren
/examples/llama.swiftui/ @ggerganov
/examples/llama.vim @ggerganov
/examples/lookahead/ @ggerganov
/examples/lookup/ @JohannesGaessler
/examples/model-conversion/ @danbev
/examples/parallel/ @ggerganov
/examples/passkey/ @ggerganov
/examples/retrieval/ @ggerganov
/examples/save-load-state/ @ggerganov
/examples/speculative-simple/ @ggerganov
/examples/speculative/ @ggerganov
/ggml/cmake/ @ggerganov
/ggml/include/ @ggerganov
/ggml/src/ggml-common.h @ggerganov
/ggml/src/ggml-cpu/ @ggerganov
/ggml/src/ggml-cpu/spacemit/ @alex-spacemit
/ggml/src/ggml-cuda/fattn* @JohannesGaessler
/ggml/src/ggml-cuda/mmf.* @JohannesGaessler @am17an
/ggml/src/ggml-cuda/mmq.* @JohannesGaessler
/ggml/src/ggml-cuda/mmvf.* @JohannesGaessler
/ggml/src/ggml-cuda/mmvq.* @JohannesGaessler
/ggml/src/ggml-cuda/fattn-wmma* @IMbackK
/ggml/src/ggml-hip/ @IMbackK
/ggml/src/ggml-cuda/vendors/hip.h @IMbackK
/ggml/src/ggml-impl.h @ggerganov
/ggml/src/ggml-metal/ @ggerganov
/ggml/src/ggml-opencl/ @lhez @max-krasnyansky
/ggml/src/ggml-hexagon/ @max-krasnyansky @lhez
/ggml/src/ggml-opt.cpp @JohannesGaessler
/ggml/src/ggml-quants.* @ggerganov
/ggml/src/ggml-rpc/ @rgerganov
/ggml/src/ggml-threading.* @ggerganov
/ggml/src/ggml-vulkan/ @0cc4m
/ggml/src/ggml-virtgpu/ @kpouget
/ggml/src/ggml-webgpu/ @reeselevine
/ggml/src/ggml-zdnn/ @taronaeo @Andreas-Krebbel @AlekseiNikiforovIBM
/ggml/src/ggml.c @ggerganov
/ggml/src/ggml.cpp @ggerganov
/ggml/src/gguf.cpp @JohannesGaessler @Green-Sky
/gguf-py/ @CISC
/media/ @ggerganov
/scripts/gen* @ggerganov
/scripts/get* @ggerganov
/scripts/sync* @ggerganov
/src/ @ggerganov
/src/llama-adapter.* @CISC
/src/llama-arch.* @CISC
/src/llama-chat.* @ngxson
/src/llama-graph.* @CISC
/src/llama-model.* @CISC
/src/llama-vocab.* @CISC
/src/models/ @CISC
/tests/ @ggerganov
/tests/test-chat-.* @pwilkin
/tools/batched-bench/ @ggerganov
/tools/cli/ @ngxson
/tools/completion/ @ggerganov
/tools/mtmd/ @ngxson
/tools/perplexity/ @ggerganov
/tools/quantize/ @ggerganov
/tools/rpc/ @rgerganov
/tools/server/* @ngxson @ggerganov # no subdir
/tools/server/webui/ @allozaur
/tools/tokenize/ @ggerganov
/tools/tts/ @ggerganov
/vendor/ @ggerganov
/AUTHORS @ggerganov
/CMakeLists.txt @ggerganov
/CONTRIBUTING.md @ggerganov
/LICENSE @ggerganov
/README.md @ggerganov
/SECURITY.md @ggerganov
/build-xcframework.sh @danbev
requirements*.txt @CISC
/ci/ @ggerganov
/.devops/*.Dockerfile @ngxson
/examples/server/ @ngxson
/ggml/src/ggml-cuda/fattn* @JohannesGaessler
/ggml/src/ggml-cuda/mmq.* @JohannesGaessler
/ggml/src/ggml-cuda/mmv.* @JohannesGaessler
/ggml/src/ggml-cuda/mmvq.* @JohannesGaessler
/ggml/src/ggml-opt.cpp @JohannesGaessler
/ggml/src/gguf.cpp @JohannesGaessler

View File

@ -1,64 +1,21 @@
# Contributors
# Pull requests (for contributors)
The project differentiates between 3 levels of contributors:
- Contributors: people who have contributed before (no special privileges)
- Collaborators (Triage): people with significant contributions, who may be responsible for some parts of the code, and are expected to maintain and review contributions for the code they own
- Maintainers: responsible for reviewing and merging PRs, after approval from the code owners
# AI Usage Policy
> [!IMPORTANT]
> This project does **not** accept pull requests that are fully or predominantly AI-generated. AI tools may be utilized solely in an assistive capacity.
>
> Detailed information regarding permissible and restricted uses of AI can be found in the [AGENTS.md](AGENTS.md) file.
Code that is initially generated by AI and subsequently edited will still be considered AI-generated. AI assistance is permissible only when the majority of the code is authored by a human contributor, with AI employed exclusively for corrections or to expand on verbose modifications that the contributor has already conceptualized (e.g., generating repeated lines with minor variations).
If AI is used to generate any portion of the code, contributors must adhere to the following requirements:
1. Explicitly disclose the manner in which AI was employed.
2. Perform a comprehensive manual review prior to submitting the pull request.
3. Be prepared to explain every line of code they submitted when asked about it by a maintainer.
4. Using AI to write pull request descriptions or to respond to human reviewers is strictly prohibited.
For more info, please refer to the [AGENTS.md](AGENTS.md) file.
# Pull requests (for contributors & collaborators)
Before submitting your PR:
- Search for existing PRs to prevent duplicating efforts
- llama.cpp uses the ggml tensor library for model evaluation. If you are unfamiliar with ggml, consider taking a look at the [examples in the ggml repository](https://github.com/ggml-org/ggml/tree/master/examples/). [simple](https://github.com/ggml-org/ggml/tree/master/examples/simple) shows the bare minimum for using ggml. [gpt-2](https://github.com/ggml-org/ggml/tree/master/examples/gpt-2) has minimal implementations for language model inference using GPT-2. [mnist](https://github.com/ggml-org/ggml/tree/master/examples/mnist) demonstrates how to train and evaluate a simple image classifier
- Test your changes:
- Execute [the full CI locally on your machine](ci/README.md) before publishing
- Verify that the perplexity and the performance are not affected negatively by your changes (use `llama-perplexity` and `llama-bench`)
- If you modified the `ggml` source, run the `test-backend-ops` tool to check whether different backend implementations of the `ggml` operators produce consistent results (this requires access to at least two different `ggml` backends)
- If you modified a `ggml` operator or added a new one, add the corresponding test cases to `test-backend-ops`
- Create separate PRs for each feature or fix:
- Avoid combining unrelated changes in a single PR
- For intricate features, consider opening a feature request first to discuss and align expectations
- When adding support for a new model or feature, focus on **CPU support only** in the initial PR unless you have a good reason not to. Add support for other backends like CUDA in follow-up PRs
- Create separate PRs for each feature or fix. Avoid combining unrelated changes in a single PR
- Consider allowing write access to your branch for faster reviews, as reviewers can push commits directly
- If your PR becomes stale, don't hesitate to ping the maintainers in the comments
After submitting your PR:
- Expect requests for modifications to ensure the code meets llama.cpp's standards for quality and long-term maintainability
- Maintainers will rely on your insights and approval when making a final decision to approve and merge a PR
- If your PR becomes stale, rebase it on top of latest `master` to get maintainers attention
- Consider adding yourself to [CODEOWNERS](CODEOWNERS) to indicate your availability for fixing related issues and reviewing related PRs
# Pull requests (for maintainers)
# Pull requests (for collaborators)
- Squash-merge PRs
- Use the following format for the squashed commit title: `<module> : <commit title> (#<issue_number>)`. For example: `utils : fix typo in utils.py (#1234)`
- Optionally pick a `<module>` from here: https://github.com/ggml-org/llama.cpp/wiki/Modules
- Let other maintainers merge their own PRs
- When merging a PR, make sure you have a good understanding of the changes
- Be mindful of maintenance: most of the work going into a feature happens after the PR is merged. If the PR author is not committed to contribute long-term, someone else needs to take responsibility (you)
Maintainers reserve the right to decline review or close pull requests for any reason, particularly under any of the following conditions:
- The proposed change is already mentioned in the roadmap or an existing issue, and it has been assigned to someone.
- The pull request duplicates an existing one.
- The contributor fails to adhere to this contributing guide.
- Consider adding yourself to [CODEOWNERS](CODEOWNERS)
# Coding guidelines
@ -157,21 +114,6 @@ Maintainers reserve the right to decline review or close pull requests for any r
#endif // FOO
```
# Code maintenance
- Existing code should have designated collaborators and/or maintainers specified in the [CODEOWNERS](CODEOWNERS) file reponsible for:
- Reviewing and merging related PRs
- Fixing related bugs
- Providing developer guidance/support
- When adding or modifying a large piece of code:
- If you are a collaborator, make sure to add yourself to [CODEOWNERS](CODEOWNERS) to indicate your availability for reviewing related PRs
- If you are a contributor, find an existing collaborator who is willing to review and maintain your code long-term
- Provide the necessary CI workflow (and hardware) to test your changes (see [ci/README.md](https://github.com/ggml-org/llama.cpp/tree/master/ci))
- New code should follow the guidelines (coding, naming, etc.) outlined in this document. Exceptions are allowed in isolated, backend-specific parts of the code that do not interface directly with the `ggml` interfaces.
_(NOTE: for legacy reasons, existing code is not required to follow this guideline)_
# Documentation
- Documentation is a community effort

View File

@ -1,6 +1,6 @@
MIT License
Copyright (c) 2023-2026 The ggml authors
Copyright (c) 2023-2024 The ggml authors
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal

1616
Makefile

File diff suppressed because it is too large Load Diff

139
README.md
View File

@ -3,12 +3,11 @@
![llama](https://user-images.githubusercontent.com/1991296/230134379-7181e485-c521-4d23-a0d6-f7b3b61ba524.png)
[![License: MIT](https://img.shields.io/badge/license-MIT-blue.svg)](https://opensource.org/licenses/MIT)
[![Release](https://img.shields.io/github/v/release/ggml-org/llama.cpp)](https://github.com/ggml-org/llama.cpp/releases)
[![Server](https://github.com/ggml-org/llama.cpp/actions/workflows/server.yml/badge.svg)](https://github.com/ggml-org/llama.cpp/actions/workflows/server.yml)
[Manifesto](https://github.com/ggml-org/llama.cpp/discussions/205) / [ggml](https://github.com/ggml-org/ggml) / [ops](https://github.com/ggml-org/llama.cpp/blob/master/docs/ops.md)
[Roadmap](https://github.com/users/ggerganov/projects/7) / [Project status](https://github.com/ggml-org/llama.cpp/discussions/3471) / [Manifesto](https://github.com/ggml-org/llama.cpp/discussions/205) / [ggml](https://github.com/ggml-org/ggml)
LLM inference in C/C++
Inference of Meta's [LLaMA](https://arxiv.org/abs/2302.13971) model (and others) in pure C/C++
## Recent API changes
@ -17,42 +16,17 @@ LLM inference in C/C++
## Hot topics
- **[guide : using the new WebUI of llama.cpp](https://github.com/ggml-org/llama.cpp/discussions/16938)**
- [guide : running gpt-oss with llama.cpp](https://github.com/ggml-org/llama.cpp/discussions/15396)
- [[FEEDBACK] Better packaging for llama.cpp to support downstream consumers 🤗](https://github.com/ggml-org/llama.cpp/discussions/15313)
- Support for the `gpt-oss` model with native MXFP4 format has been added | [PR](https://github.com/ggml-org/llama.cpp/pull/15091) | [Collaboration with NVIDIA](https://blogs.nvidia.com/blog/rtx-ai-garage-openai-oss) | [Comment](https://github.com/ggml-org/llama.cpp/discussions/15095)
- Multimodal support arrived in `llama-server`: [#12898](https://github.com/ggml-org/llama.cpp/pull/12898) | [documentation](./docs/multimodal.md)
- **GGML developer experience survey (organized and reviewed by NVIDIA):** [link](https://forms.gle/Gasw3cRgyhNEnrwK9)
- A new binary `llama-mtmd-cli` is introduced to replace `llava-cli`, `minicpmv-cli`, `gemma3-cli` ([#13012](https://github.com/ggml-org/llama.cpp/pull/13012)) and `qwen2vl-cli` ([#13141]((https://github.com/ggml-org/llama.cpp/pull/13141))), `libllava` will be deprecated
- VS Code extension for FIM completions: https://github.com/ggml-org/llama.vscode
- Universal [tool call support](./docs/function-calling.md) in `llama-server` https://github.com/ggml-org/llama.cpp/pull/9639
- Vim/Neovim plugin for FIM completions: https://github.com/ggml-org/llama.vim
- Introducing GGUF-my-LoRA https://github.com/ggml-org/llama.cpp/discussions/10123
- Hugging Face Inference Endpoints now support GGUF out of the box! https://github.com/ggml-org/llama.cpp/discussions/9669
- Hugging Face GGUF editor: [discussion](https://github.com/ggml-org/llama.cpp/discussions/9268) | [tool](https://huggingface.co/spaces/CISCai/gguf-editor)
----
## Quick start
Getting started with llama.cpp is straightforward. Here are several ways to install it on your machine:
- Install `llama.cpp` using [brew, nix or winget](docs/install.md)
- Run with Docker - see our [Docker documentation](docs/docker.md)
- Download pre-built binaries from the [releases page](https://github.com/ggml-org/llama.cpp/releases)
- Build from source by cloning this repository - check out [our build guide](docs/build.md)
Once installed, you'll need a model to work with. Head to the [Obtaining and quantizing models](#obtaining-and-quantizing-models) section to learn more.
Example command:
```sh
# Use a local model file
llama-cli -m my_model.gguf
# Or download and run a model directly from Hugging Face
llama-cli -hf ggml-org/gemma-3-1b-it-GGUF
# Launch OpenAI-compatible API server
llama-server -hf ggml-org/gemma-3-1b-it-GGUF
```
## Description
The main goal of `llama.cpp` is to enable LLM inference with minimal setup and state-of-the-art performance on a wide
@ -61,9 +35,8 @@ range of hardware - locally and in the cloud.
- Plain C/C++ implementation without any dependencies
- Apple silicon is a first-class citizen - optimized via ARM NEON, Accelerate and Metal frameworks
- AVX, AVX2, AVX512 and AMX support for x86 architectures
- RVV, ZVFH, ZFH, ZICBOP and ZIHINTPAUSE support for RISC-V architectures
- 1.5-bit, 2-bit, 3-bit, 4-bit, 5-bit, 6-bit, and 8-bit integer quantization for faster inference and reduced memory use
- Custom CUDA kernels for running LLMs on NVIDIA GPUs (support for AMD GPUs via HIP and Moore Threads GPUs via MUSA)
- Custom CUDA kernels for running LLMs on NVIDIA GPUs (support for AMD GPUs via HIP and Moore Threads MTT GPUs via MUSA)
- Vulkan and SYCL backend support
- CPU+GPU hybrid inference to partially accelerate models larger than the total VRAM capacity
@ -84,7 +57,6 @@ Instructions for adding support for new models: [HOWTO-add-model.md](docs/develo
- [X] [Mistral 7B](https://huggingface.co/mistralai/Mistral-7B-v0.1)
- [x] [Mixtral MoE](https://huggingface.co/models?search=mistral-ai/Mixtral)
- [x] [DBRX](https://huggingface.co/databricks/dbrx-instruct)
- [x] [Jamba](https://huggingface.co/ai21labs)
- [X] [Falcon](https://huggingface.co/models?search=tiiuae/falcon)
- [X] [Chinese LLaMA / Alpaca](https://github.com/ymcui/Chinese-LLaMA-Alpaca) and [Chinese LLaMA-2 / Alpaca-2](https://github.com/ymcui/Chinese-LLaMA-Alpaca-2)
- [X] [Vigogne (French)](https://github.com/bofenghuang/vigogne)
@ -132,15 +104,11 @@ Instructions for adding support for new models: [HOWTO-add-model.md](docs/develo
- [x] [FalconMamba Models](https://huggingface.co/collections/tiiuae/falconmamba-7b-66b9a580324dd1598b0f6d4a)
- [x] [Jais](https://huggingface.co/inceptionai/jais-13b-chat)
- [x] [Bielik-11B-v2.3](https://huggingface.co/collections/speakleash/bielik-11b-v23-66ee813238d9b526a072408a)
- [x] [RWKV-7](https://huggingface.co/collections/shoumenchougou/rwkv7-gxx-gguf)
- [x] [RWKV-6](https://github.com/BlinkDL/RWKV-LM)
- [x] [QRWKV-6](https://huggingface.co/recursal/QRWKV6-32B-Instruct-Preview-v0.1)
- [x] [GigaChat-20B-A3B](https://huggingface.co/ai-sage/GigaChat-20B-A3B-instruct)
- [X] [Trillion-7B-preview](https://huggingface.co/trillionlabs/Trillion-7B-preview)
- [x] [Ling models](https://huggingface.co/collections/inclusionAI/ling-67c51c85b34a7ea0aba94c32)
- [x] [LFM2 models](https://huggingface.co/collections/LiquidAI/lfm2-686d721927015b2ad73eaa38)
- [x] [Hunyuan models](https://huggingface.co/collections/tencent/hunyuan-dense-model-6890632cda26b19119c9c5e7)
- [x] [BailingMoeV2 (Ring/Ling 2.0) models](https://huggingface.co/collections/inclusionAI/ling-v2-68bf1dd2fc34c306c1fa6f86)
#### Multimodal
@ -155,14 +123,12 @@ Instructions for adding support for new models: [HOWTO-add-model.md](docs/develo
- [x] [Bunny](https://github.com/BAAI-DCAI/Bunny)
- [x] [GLM-EDGE](https://huggingface.co/models?search=glm-edge)
- [x] [Qwen2-VL](https://huggingface.co/collections/Qwen/qwen2-vl-66cee7455501d7126940800d)
- [x] [LFM2-VL](https://huggingface.co/collections/LiquidAI/lfm2-vl-68963bbc84a610f7638d5ffa)
</details>
<details>
<summary>Bindings</summary>
- Python: [ddh0/easy-llama](https://github.com/ddh0/easy-llama)
- Python: [abetlen/llama-cpp-python](https://github.com/abetlen/llama-cpp-python)
- Go: [go-skynet/go-llama.cpp](https://github.com/go-skynet/go-llama.cpp)
- Node.js: [withcatai/node-llama-cpp](https://github.com/withcatai/node-llama-cpp)
@ -181,7 +147,6 @@ Instructions for adding support for new models: [HOWTO-add-model.md](docs/develo
- Clojure: [phronmophobic/llama.clj](https://github.com/phronmophobic/llama.clj)
- React Native: [mybigday/llama.rn](https://github.com/mybigday/llama.rn)
- Java: [kherud/java-llama.cpp](https://github.com/kherud/java-llama.cpp)
- Java: [QuasarByte/llama-cpp-jna](https://github.com/QuasarByte/llama-cpp-jna)
- Zig: [deins/llama.cpp.zig](https://github.com/Deins/llama.cpp.zig)
- Flutter/Dart: [netdur/llama_cpp_dart](https://github.com/netdur/llama_cpp_dart)
- Flutter: [xuegao-tzx/Fllama](https://github.com/xuegao-tzx/Fllama)
@ -190,8 +155,6 @@ Instructions for adding support for new models: [HOWTO-add-model.md](docs/develo
- Swift [srgtuszy/llama-cpp-swift](https://github.com/srgtuszy/llama-cpp-swift)
- Swift [ShenghaiWang/SwiftLlama](https://github.com/ShenghaiWang/SwiftLlama)
- Delphi [Embarcadero/llama-cpp-delphi](https://github.com/Embarcadero/llama-cpp-delphi)
- Go (no CGo needed): [hybridgroup/yzma](https://github.com/hybridgroup/yzma)
- Android: [llama.android](/examples/llama.android)
</details>
@ -201,7 +164,6 @@ Instructions for adding support for new models: [HOWTO-add-model.md](docs/develo
*(to have a project listed here, it should clearly state that it depends on `llama.cpp`)*
- [AI Sublime Text plugin](https://github.com/yaroslavyaroslav/OpenAI-sublime-text) (MIT)
- [BonzAI App](https://apps.apple.com/us/app/bonzai-your-local-ai-agent/id6752847988) (proprietary)
- [cztomsik/ava](https://github.com/cztomsik/ava) (MIT)
- [Dot](https://github.com/alexpinel/Dot) (GPL)
- [eva](https://github.com/ylsdamxssjxxdd/eva) (MIT)
@ -213,7 +175,6 @@ Instructions for adding support for new models: [HOWTO-add-model.md](docs/develo
- [llama.vim](https://github.com/ggml-org/llama.vim) (MIT)
- [LARS](https://github.com/abgulati/LARS) (AGPL)
- [Llama Assistant](https://github.com/vietanhdev/llama-assistant) (GPL)
- [LlamaLib](https://github.com/undreamai/LlamaLib) (Apache-2.0)
- [LLMFarm](https://github.com/guinmoon/LLMFarm?tab=readme-ov-file) (MIT)
- [LLMUnity](https://github.com/undreamai/LLMUnity) (MIT)
- [LMStudio](https://lmstudio.ai/) (proprietary)
@ -246,14 +207,13 @@ Instructions for adding support for new models: [HOWTO-add-model.md](docs/develo
- [crashr/gppm](https://github.com/crashr/gppm) launch llama.cpp instances utilizing NVIDIA Tesla P40 or P100 GPUs with reduced idle power consumption
- [gpustack/gguf-parser](https://github.com/gpustack/gguf-parser-go/tree/main/cmd/gguf-parser) - review/check the GGUF file and estimate the memory usage
- [Styled Lines](https://marketplace.unity.com/packages/tools/generative-ai/styled-lines-llama-cpp-model-292902) (proprietary licensed, async wrapper of inference part for game development in Unity3d with pre-built Mobile and Web platform wrappers and a model example)
- [unslothai/unsloth](https://github.com/unslothai/unsloth) 🦥 exports/saves fine-tuned and trained models to GGUF (Apache-2.0)
</details>
<details>
<summary>Infrastructure</summary>
- [Paddler](https://github.com/intentee/paddler) - Open-source LLMOps platform for hosting and scaling AI in your own infrastructure
- [Paddler](https://github.com/distantmagic/paddler) - Stateful load balancer custom-tailored for llama.cpp
- [GPUStack](https://github.com/gpustack/gpustack) - Manage GPU clusters for running LLMs
- [llama_cpp_canister](https://github.com/onicai/llama_cpp_canister) - llama.cpp as a smart contract on the Internet Computer, using WebAssembly
- [llama-swap](https://github.com/mostlygeek/llama-swap) - transparent proxy that adds automatic model switching with llama-server
@ -268,7 +228,6 @@ Instructions for adding support for new models: [HOWTO-add-model.md](docs/develo
</details>
## Supported backends
| Backend | Target devices |
@ -277,17 +236,23 @@ Instructions for adding support for new models: [HOWTO-add-model.md](docs/develo
| [BLAS](docs/build.md#blas-build) | All |
| [BLIS](docs/backend/BLIS.md) | All |
| [SYCL](docs/backend/SYCL.md) | Intel and Nvidia GPU |
| [MUSA](docs/build.md#musa) | Moore Threads GPU |
| [MUSA](docs/build.md#musa) | Moore Threads MTT GPU |
| [CUDA](docs/build.md#cuda) | Nvidia GPU |
| [HIP](docs/build.md#hip) | AMD GPU |
| [ZenDNN](docs/build.md#zendnn) | AMD CPU |
| [Vulkan](docs/build.md#vulkan) | GPU |
| [CANN](docs/build.md#cann) | Ascend NPU |
| [OpenCL](docs/backend/OPENCL.md) | Adreno GPU |
| [IBM zDNN](docs/backend/zDNN.md) | IBM Z & LinuxONE |
| [WebGPU [In Progress]](docs/build.md#webgpu) | All |
| [RPC](https://github.com/ggml-org/llama.cpp/tree/master/tools/rpc) | All |
| [Hexagon [In Progress]](docs/backend/hexagon/README.md) | Snapdragon |
| [RPC](https://github.com/ggml-org/llama.cpp/tree/master/examples/rpc) | All |
## Building the project
The main product of this project is the `llama` library. Its C-style interface can be found in [include/llama.h](include/llama.h).
The project also includes many example programs and tools using the `llama` library. The examples range from simple, minimal code snippets to sophisticated sub-projects such as an OpenAI-compatible HTTP server. Possible methods for obtaining the binaries:
- Clone this repository and build locally, see [how to build](docs/build.md)
- On MacOS or Linux, install `llama.cpp` via [brew, flox or nix](docs/install.md)
- Use a Docker image, see [documentation for Docker](docs/docker.md)
- Download pre-built binaries from [releases](https://github.com/ggml-org/llama.cpp/releases)
## Obtaining and quantizing models
@ -296,11 +261,7 @@ The [Hugging Face](https://huggingface.co) platform hosts a [number of LLMs](htt
- [Trending](https://huggingface.co/models?library=gguf&sort=trending)
- [LLaMA](https://huggingface.co/models?sort=trending&search=llama+gguf)
You can either manually download the GGUF file or directly use any `llama.cpp`-compatible models from [Hugging Face](https://huggingface.co/) or other model hosting sites, such as [ModelScope](https://modelscope.cn/), by using this CLI argument: `-hf <user>/<model>[:quant]`. For example:
```sh
llama-cli -hf ggml-org/gemma-3-1b-it-GGUF
```
You can either manually download the GGUF file or directly use any `llama.cpp`-compatible models from [Hugging Face](https://huggingface.co/) or other model hosting sites, such as [ModelScope](https://modelscope.cn/), by using this CLI argument: `-hf <user>/<model>[:quant]`.
By default, the CLI would download from Hugging Face, you can switch to other options with the environment variable `MODEL_ENDPOINT`. For example, you may opt to downloading model checkpoints from ModelScope or other model sharing communities by setting the environment variable, e.g. `MODEL_ENDPOINT=https://www.modelscope.cn/`.
@ -315,9 +276,9 @@ The Hugging Face platform provides a variety of online tools for converting, qua
- Use the [GGUF-editor space](https://huggingface.co/spaces/CISCai/gguf-editor) to edit GGUF meta data in the browser (more info: https://github.com/ggml-org/llama.cpp/discussions/9268)
- Use the [Inference Endpoints](https://ui.endpoints.huggingface.co/) to directly host `llama.cpp` in the cloud (more info: https://github.com/ggml-org/llama.cpp/discussions/9669)
To learn more about model quantization, [read this documentation](tools/quantize/README.md)
To learn more about model quantization, [read this documentation](examples/quantize/README.md)
## [`llama-cli`](tools/cli)
## [`llama-cli`](examples/main)
#### A CLI tool for accessing and experimenting with most of `llama.cpp`'s functionality.
@ -351,6 +312,19 @@ To learn more about model quantization, [read this documentation](tools/quantize
</details>
- <details>
<summary>Run simple text completion</summary>
To disable conversation mode explicitly, use `-no-cnv`
```bash
llama-cli -m model.gguf -p "I believe the meaning of life is" -n 128 -no-cnv
# I believe the meaning of life is to find your own truth and to live in accordance with it. For me, this means being true to myself and following my passions, even if they don't align with societal expectations. I think that's what I love about yoga it's not just a physical practice, but a spiritual one too. It's about connecting with yourself, listening to your inner voice, and honoring your own unique journey.
```
</details>
- <details>
<summary>Constrain the output with a custom grammar</summary>
@ -367,7 +341,7 @@ To learn more about model quantization, [read this documentation](tools/quantize
</details>
## [`llama-server`](tools/server)
## [`llama-server`](examples/server)
#### A lightweight, [OpenAI API](https://github.com/openai/openai-openapi) compatible, HTTP server for serving LLMs.
@ -437,9 +411,9 @@ To learn more about model quantization, [read this documentation](tools/quantize
</details>
## [`llama-perplexity`](tools/perplexity)
## [`llama-perplexity`](examples/perplexity)
#### A tool for measuring the [perplexity](tools/perplexity/README.md) [^1] (and other quality metrics) of a model over a given text.
#### A tool for measuring the perplexity [^1][^2] (and other quality metrics) of a model over a given text.
- <details open>
<summary>Measure the perplexity over a text file</summary>
@ -462,9 +436,10 @@ To learn more about model quantization, [read this documentation](tools/quantize
</details>
[^1]: [https://huggingface.co/docs/transformers/perplexity](https://huggingface.co/docs/transformers/perplexity)
[^1]: [examples/perplexity/README.md](./examples/perplexity/README.md)
[^2]: [https://huggingface.co/docs/transformers/perplexity](https://huggingface.co/docs/transformers/perplexity)
## [`llama-bench`](tools/llama-bench)
## [`llama-bench`](examples/llama-bench)
#### Benchmark the performance of the inference for various parameters.
@ -485,6 +460,21 @@ To learn more about model quantization, [read this documentation](tools/quantize
</details>
## [`llama-run`](examples/run)
#### A comprehensive example for running `llama.cpp` models. Useful for inferencing. Used with RamaLama [^3].
- <details>
<summary>Run a model with a specific prompt (by default it's pulled from Ollama registry)</summary>
```bash
llama-run granite-code
```
</details>
[^3]: [RamaLama](https://github.com/containers/ramalama)
## [`llama-simple`](examples/simple)
#### A minimal example for implementing apps with `llama.cpp`. Useful for developers.
@ -504,8 +494,8 @@ To learn more about model quantization, [read this documentation](tools/quantize
## Contributing
- Contributors can open PRs
- Collaborators can push to branches in the `llama.cpp` repo and merge PRs into the `master` branch
- Collaborators will be invited based on contributions
- Maintainers can push to branches in the `llama.cpp` repo and merge PRs into the `master` branch
- Any help with managing issues, PRs and projects is very appreciated!
- See [good first issues](https://github.com/ggml-org/llama.cpp/issues?q=is%3Aissue+is%3Aopen+label%3A%22good+first+issue%22) for tasks suitable for first contributions
- Read the [CONTRIBUTING.md](CONTRIBUTING.md) for more information
@ -514,9 +504,8 @@ To learn more about model quantization, [read this documentation](tools/quantize
## Other documentation
- [cli](tools/cli/README.md)
- [completion](tools/completion/README.md)
- [server](tools/server/README.md)
- [main (cli)](examples/main/README.md)
- [server](examples/server/README.md)
- [GBNF grammars](grammars/README.md)
#### Development documentation
@ -582,10 +571,4 @@ automatically. For example:
$ echo "source ~/.llama-completion.bash" >> ~/.bashrc
```
## Dependencies
- [yhirose/cpp-httplib](https://github.com/yhirose/cpp-httplib) - Single-header HTTP server, used by `llama-server` - MIT license
- [stb-image](https://github.com/nothings/stb) - Single-header image format decoder, used by multimodal subsystem - Public domain
- [nlohmann/json](https://github.com/nlohmann/json) - Single-header JSON library, used by various tools/examples - MIT License
- [miniaudio.h](https://github.com/mackron/miniaudio) - Single-header audio format decoder, used by multimodal subsystem - Public domain
- [subprocess.h](https://github.com/sheredom/subprocess.h) - Single-header process launching solution for C and C++ - Public domain
## References

View File

@ -1,52 +1,12 @@
# Security Policy
- [**Reporting a vulnerability**](#reporting-a-vulnerability)
- [**Requirements**](#requirements)
- [**Covered Topics**](#covered-topics)
- [**Using llama.cpp securely**](#using-llamacpp-securely)
- [Untrusted models](#untrusted-models)
- [Untrusted inputs](#untrusted-inputs)
- [Data privacy](#data-privacy)
- [Untrusted environments or networks](#untrusted-environments-or-networks)
- [Multi-Tenant environments](#multi-tenant-environments)
## Reporting a vulnerability
If you have discovered a security vulnerability in this project that falls inside the [covered topics](#covered-topics), please report it privately. **Do not disclose it as a public issue.** This gives us time to work with you to fix the issue before public exposure, reducing the chance that the exploit will be used before a patch is released.
Please disclose it as a private [security advisory](https://github.com/ggml-org/llama.cpp/security/advisories/new).
A team of volunteers on a reasonable-effort basis maintains this project. As such, please give us at least 90 days to work on a fix before public exposure.
> [!IMPORTANT]
> For collaborators: if you are interested in helping out with reviewing privting security disclosures, please see: https://github.com/ggml-org/llama.cpp/discussions/18080
## Requirements
Before submitting your report, ensure you meet the following requirements:
- You have read this policy and fully understand it.
- AI is only permitted in an assistive capacity as stated in [AGENTS.md](AGENTS.md). We do not accept reports that are written exclusively by AI.
- Your report must include a working Proof-of-Concept in the form of a script and/or attached files.
Maintainers reserve the right to close the report if these requirements are not fulfilled.
## Covered Topics
Only vulnerabilities that fall within these parts of the project are considered valid. For problems falling outside of this list, please report them as issues.
- `src/**/*`
- `ggml/**/*`
- `gguf-py/**/*`
- `tools/server/*`, **excluding** the following topics:
- Web UI
- Features marked as experimental
- Features not recommended for use in untrusted environments (e.g., router, MCP)
- Bugs that can lead to Denial-of-Service attack
Note that none of the topics under [Using llama.cpp securely](#using-llamacpp-securely) are considered vulnerabilities in LLaMA C++.
For vulnerabilities that fall within the `vendor` directory, please report them directly to the third-party project.
- [**Reporting a vulnerability**](#reporting-a-vulnerability)
## Using llama.cpp securely
@ -80,7 +40,7 @@ To protect sensitive data from potential leaks or unauthorized access, it is cru
### Untrusted environments or networks
If you can't run your models in a secure and isolated environment or if it must be exposed to an untrusted network, make sure to take the following security precautions:
* Do not use the RPC backend, [rpc-server](https://github.com/ggml-org/llama.cpp/tree/master/tools/rpc) and [llama-server](https://github.com/ggml-org/llama.cpp/tree/master/tools/server) functionality (see https://github.com/ggml-org/llama.cpp/pull/13061).
* Do not use the RPC backend, [rpc-server](https://github.com/ggml-org/llama.cpp/tree/master/examples/rpc) and [llama-server](https://github.com/ggml-org/llama.cpp/tree/master/examples/server) functionality (see https://github.com/ggml-org/llama.cpp/pull/13061).
* Confirm the hash of any downloaded artifact (e.g. pre-trained model weights) matches a known-good value.
* Encrypt your data if sending it over the network.
@ -95,3 +55,14 @@ If you intend to run multiple models in parallel with shared memory, it is your
3. Model Sharing: In a multitenant model sharing design, tenants and users must understand the security risks of running code provided by others. Since there are no reliable methods to detect malicious models, sandboxing the model execution is the recommended approach to mitigate the risk.
4. Hardware Attacks: GPUs or TPUs can also be attacked. [Researches](https://scholar.google.com/scholar?q=gpu+side+channel) has shown that side channel attacks on GPUs are possible, which can make data leak from other models or processes running on the same system at the same time.
## Reporting a vulnerability
Beware that none of the topics under [Using llama.cpp securely](#using-llamacpp-securely) are considered vulnerabilities of LLaMA C++.
<!-- normal version -->
However, If you have discovered a security vulnerability in this project, please report it privately. **Do not disclose it as a public issue.** This gives us time to work with you to fix the issue before public exposure, reducing the chance that the exploit will be used before a patch is released.
Please disclose it as a private [security advisory](https://github.com/ggml-org/llama.cpp/security/advisories/new).
A team of volunteers on a reasonable-effort basis maintains this project. As such, please give us at least 90 days to work on a fix before public exposure.

View File

@ -1,6 +0,0 @@
{
"chars": 2296.1916666666666,
"chars:std": 986.051306946325,
"score": 0.925,
"score:std": 0.26339134382131846
}

File diff suppressed because one or more lines are too long

View File

@ -1,311 +0,0 @@
## System info
```bash
uname --all
Linux spark-17ed 6.11.0-1016-nvidia #16-Ubuntu SMP PREEMPT_DYNAMIC Sun Sep 21 16:52:46 UTC 2025 aarch64 aarch64 aarch64 GNU/Linux
g++ --version
g++ (Ubuntu 13.3.0-6ubuntu2~24.04) 13.3.0
nvidia-smi
Thu Feb 5 13:49:40 2026
+-----------------------------------------------------------------------------------------+
| NVIDIA-SMI 580.95.05 Driver Version: 580.95.05 CUDA Version: 13.0 |
+-----------------------------------------+------------------------+----------------------+
| GPU Name Persistence-M | Bus-Id Disp.A | Volatile Uncorr. ECC |
| Fan Temp Perf Pwr:Usage/Cap | Memory-Usage | GPU-Util Compute M. |
| | | MIG M. |
|=========================================+========================+======================|
| 0 NVIDIA GB10 On | 0000000F:01:00.0 Off | N/A |
| N/A 47C P0 13W / N/A | Not Supported | 0% Default |
| | | N/A |
+-----------------------------------------+------------------------+----------------------+
```
## ggml-org/gpt-oss-20b-GGUF
Model: https://huggingface.co/ggml-org/gpt-oss-20b-GGUF
- `llama-batched-bench`
main: n_kv_max = 270336, n_batch = 2048, n_ubatch = 2048, flash_attn = 1, is_pp_shared = 0, is_tg_separate = 0, n_gpu_layers = -1, n_threads = 20, n_threads_batch = 20
| PP | TG | B | N_KV | T_PP s | S_PP t/s | T_TG s | S_TG t/s | T s | S t/s |
|-------|--------|------|--------|----------|----------|----------|----------|----------|----------|
| 512 | 32 | 1 | 544 | 0.270 | 1895.57 | 0.399 | 80.13 | 0.669 | 812.60 |
| 512 | 32 | 2 | 1088 | 0.230 | 4451.23 | 0.583 | 109.71 | 0.813 | 1337.56 |
| 512 | 32 | 4 | 2176 | 0.437 | 4688.87 | 0.820 | 156.03 | 1.257 | 1730.91 |
| 512 | 32 | 8 | 4352 | 0.863 | 4744.23 | 0.942 | 271.79 | 1.805 | 2410.73 |
| 512 | 32 | 16 | 8704 | 1.725 | 4748.19 | 1.173 | 436.38 | 2.899 | 3002.85 |
| 512 | 32 | 32 | 17408 | 3.437 | 4767.38 | 1.503 | 681.49 | 4.939 | 3524.40 |
| 4096 | 32 | 1 | 4128 | 0.907 | 4513.91 | 0.407 | 78.54 | 1.315 | 3139.56 |
| 4096 | 32 | 2 | 8256 | 1.796 | 4560.42 | 0.625 | 102.37 | 2.422 | 3409.45 |
| 4096 | 32 | 4 | 16512 | 3.596 | 4555.66 | 0.888 | 144.11 | 4.485 | 3681.93 |
| 4096 | 32 | 8 | 33024 | 7.184 | 4561.44 | 1.098 | 233.11 | 8.282 | 3987.51 |
| 4096 | 32 | 16 | 66048 | 14.369 | 4560.82 | 1.503 | 340.74 | 15.872 | 4161.30 |
| 4096 | 32 | 32 | 132096 | 28.760 | 4557.52 | 2.162 | 473.59 | 30.922 | 4271.95 |
| 8192 | 32 | 1 | 8224 | 1.859 | 4405.59 | 0.430 | 74.36 | 2.290 | 3591.61 |
| 8192 | 32 | 2 | 16448 | 3.698 | 4430.02 | 0.656 | 97.59 | 4.354 | 3777.47 |
| 8192 | 32 | 4 | 32896 | 7.403 | 4426.10 | 0.957 | 133.82 | 8.360 | 3934.97 |
| 8192 | 32 | 8 | 65792 | 14.802 | 4427.63 | 1.222 | 209.44 | 16.024 | 4105.87 |
| 8192 | 32 | 16 | 131584 | 29.596 | 4428.67 | 1.741 | 294.13 | 31.337 | 4199.00 |
| 8192 | 32 | 32 | 263168 | 59.169 | 4430.42 | 2.619 | 390.92 | 61.789 | 4259.17 |
- `llama-bench`
| model | size | params | backend | ngl | n_ubatch | fa | mmap | dio | test | t/s |
| ------------------------------ | ---------: | ---------: | ---------- | --: | -------: | -: | ---: | --: | --------------: | -------------------: |
| gpt-oss 20B MXFP4 MoE | 11.27 GiB | 20.91 B | CUDA | 99 | 2048 | 1 | 0 | 1 | pp2048 | 4505.82 ± 12.90 |
| gpt-oss 20B MXFP4 MoE | 11.27 GiB | 20.91 B | CUDA | 99 | 2048 | 1 | 0 | 1 | tg32 | 83.43 ± 0.59 |
| gpt-oss 20B MXFP4 MoE | 11.27 GiB | 20.91 B | CUDA | 99 | 2048 | 1 | 0 | 1 | pp2048 @ d4096 | 4158.34 ± 18.84 |
| gpt-oss 20B MXFP4 MoE | 11.27 GiB | 20.91 B | CUDA | 99 | 2048 | 1 | 0 | 1 | tg32 @ d4096 | 79.22 ± 0.60 |
| gpt-oss 20B MXFP4 MoE | 11.27 GiB | 20.91 B | CUDA | 99 | 2048 | 1 | 0 | 1 | pp2048 @ d8192 | 3993.81 ± 17.55 |
| gpt-oss 20B MXFP4 MoE | 11.27 GiB | 20.91 B | CUDA | 99 | 2048 | 1 | 0 | 1 | tg32 @ d8192 | 75.22 ± 1.05 |
| gpt-oss 20B MXFP4 MoE | 11.27 GiB | 20.91 B | CUDA | 99 | 2048 | 1 | 0 | 1 | pp2048 @ d16384 | 3449.98 ± 12.13 |
| gpt-oss 20B MXFP4 MoE | 11.27 GiB | 20.91 B | CUDA | 99 | 2048 | 1 | 0 | 1 | tg32 @ d16384 | 70.36 ± 0.37 |
| gpt-oss 20B MXFP4 MoE | 11.27 GiB | 20.91 B | CUDA | 99 | 2048 | 1 | 0 | 1 | pp2048 @ d32768 | 2689.42 ± 18.89 |
| gpt-oss 20B MXFP4 MoE | 11.27 GiB | 20.91 B | CUDA | 99 | 2048 | 1 | 0 | 1 | tg32 @ d32768 | 61.65 ± 0.30 |
build: 11fb327bf (7941)
## ggml-org/gpt-oss-120b-GGUF
Model: https://huggingface.co/ggml-org/gpt-oss-120b-GGUF
- `llama-batched-bench`
main: n_kv_max = 270336, n_batch = 2048, n_ubatch = 2048, flash_attn = 1, is_pp_shared = 0, is_tg_separate = 0, n_gpu_layers = -1, n_threads = 20, n_threads_batch = 20
| PP | TG | B | N_KV | T_PP s | S_PP t/s | T_TG s | S_TG t/s | T s | S t/s |
|-------|--------|------|--------|----------|----------|----------|----------|----------|----------|
| 512 | 32 | 1 | 544 | 0.445 | 1151.80 | 0.560 | 57.14 | 1.005 | 541.53 |
| 512 | 32 | 2 | 1088 | 0.472 | 2169.85 | 0.874 | 73.27 | 1.345 | 808.65 |
| 512 | 32 | 4 | 2176 | 0.826 | 2480.33 | 1.299 | 98.51 | 2.125 | 1023.94 |
| 512 | 32 | 8 | 4352 | 1.644 | 2491.67 | 1.608 | 159.18 | 3.252 | 1338.20 |
| 512 | 32 | 16 | 8704 | 3.292 | 2488.35 | 2.117 | 241.85 | 5.409 | 1609.13 |
| 512 | 32 | 32 | 17408 | 6.604 | 2481.07 | 2.898 | 353.31 | 9.502 | 1832.04 |
| 4096 | 32 | 1 | 4128 | 1.698 | 2412.65 | 0.580 | 55.21 | 2.277 | 1812.66 |
| 4096 | 32 | 2 | 8256 | 3.399 | 2409.88 | 0.934 | 68.53 | 4.333 | 1905.27 |
| 4096 | 32 | 4 | 16512 | 6.823 | 2401.21 | 1.411 | 90.72 | 8.234 | 2005.30 |
| 4096 | 32 | 8 | 33024 | 13.574 | 2413.97 | 1.841 | 139.07 | 15.415 | 2142.31 |
| 4096 | 32 | 16 | 66048 | 27.176 | 2411.52 | 2.609 | 196.26 | 29.785 | 2217.49 |
| 4096 | 32 | 32 | 132096 | 54.359 | 2411.23 | 3.905 | 262.20 | 58.264 | 2267.19 |
| 8192 | 32 | 1 | 8224 | 3.491 | 2346.81 | 0.613 | 52.23 | 4.103 | 2004.21 |
| 8192 | 32 | 2 | 16448 | 6.939 | 2361.03 | 0.981 | 65.21 | 7.921 | 2076.56 |
| 8192 | 32 | 4 | 32896 | 13.888 | 2359.40 | 1.511 | 84.71 | 15.399 | 2136.21 |
| 8192 | 32 | 8 | 65792 | 27.756 | 2361.18 | 2.034 | 125.86 | 29.790 | 2208.56 |
| 8192 | 32 | 16 | 131584 | 55.554 | 2359.34 | 3.021 | 169.49 | 58.575 | 2246.41 |
| 8192 | 32 | 32 | 263168 | 111.036 | 2360.89 | 4.537 | 225.72 | 115.573 | 2277.08 |
- `llama-bench`
| model | size | params | backend | ngl | n_ubatch | fa | mmap | dio | test | t/s |
| ------------------------------ | ---------: | ---------: | ---------- | --: | -------: | -: | ---: | --: | --------------: | -------------------: |
| gpt-oss 120B MXFP4 MoE | 59.02 GiB | 116.83 B | CUDA | 99 | 2048 | 1 | 0 | 1 | pp2048 | 2443.91 ± 7.47 |
| gpt-oss 120B MXFP4 MoE | 59.02 GiB | 116.83 B | CUDA | 99 | 2048 | 1 | 0 | 1 | tg32 | 58.72 ± 0.20 |
| gpt-oss 120B MXFP4 MoE | 59.02 GiB | 116.83 B | CUDA | 99 | 2048 | 1 | 0 | 1 | pp2048 @ d4096 | 2309.84 ± 3.63 |
| gpt-oss 120B MXFP4 MoE | 59.02 GiB | 116.83 B | CUDA | 99 | 2048 | 1 | 0 | 1 | tg32 @ d4096 | 55.67 ± 0.35 |
| gpt-oss 120B MXFP4 MoE | 59.02 GiB | 116.83 B | CUDA | 99 | 2048 | 1 | 0 | 1 | pp2048 @ d8192 | 2216.68 ± 10.16 |
| gpt-oss 120B MXFP4 MoE | 59.02 GiB | 116.83 B | CUDA | 99 | 2048 | 1 | 0 | 1 | tg32 @ d8192 | 52.87 ± 0.43 |
| gpt-oss 120B MXFP4 MoE | 59.02 GiB | 116.83 B | CUDA | 99 | 2048 | 1 | 0 | 1 | pp2048 @ d16384 | 1956.31 ± 6.39 |
| gpt-oss 120B MXFP4 MoE | 59.02 GiB | 116.83 B | CUDA | 99 | 2048 | 1 | 0 | 1 | tg32 @ d16384 | 49.45 ± 0.20 |
| gpt-oss 120B MXFP4 MoE | 59.02 GiB | 116.83 B | CUDA | 99 | 2048 | 1 | 0 | 1 | pp2048 @ d32768 | 1567.08 ± 11.79 |
| gpt-oss 120B MXFP4 MoE | 59.02 GiB | 116.83 B | CUDA | 99 | 2048 | 1 | 0 | 1 | tg32 @ d32768 | 42.76 ± 0.14 |
build: 11fb327bf (7941)
## ggml-org/Qwen3-Coder-30B-A3B-Instruct-Q8_0-GGUF
Model: https://huggingface.co/ggml-org/Qwen3-Coder-30B-A3B-Instruct-Q8_0-GGUF
- `llama-batched-bench`
main: n_kv_max = 270336, n_batch = 2048, n_ubatch = 2048, flash_attn = 1, is_pp_shared = 0, is_tg_separate = 0, n_gpu_layers = -1, n_threads = 20, n_threads_batch = 20
| PP | TG | B | N_KV | T_PP s | S_PP t/s | T_TG s | S_TG t/s | T s | S t/s |
|-------|--------|------|--------|----------|----------|----------|----------|----------|----------|
| 512 | 32 | 1 | 544 | 0.393 | 1303.73 | 0.548 | 58.36 | 0.941 | 578.10 |
| 512 | 32 | 2 | 1088 | 0.387 | 2648.68 | 0.910 | 70.35 | 1.296 | 839.27 |
| 512 | 32 | 4 | 2176 | 0.659 | 3107.63 | 1.302 | 98.33 | 1.961 | 1109.77 |
| 512 | 32 | 8 | 4352 | 1.322 | 3099.35 | 1.669 | 153.42 | 2.990 | 1455.43 |
| 512 | 32 | 16 | 8704 | 2.639 | 3104.63 | 2.212 | 231.44 | 4.851 | 1794.32 |
| 512 | 32 | 32 | 17408 | 5.284 | 3100.80 | 2.955 | 346.53 | 8.239 | 2112.93 |
| 4096 | 32 | 1 | 4128 | 1.417 | 2890.36 | 0.598 | 53.51 | 2.015 | 2048.45 |
| 4096 | 32 | 2 | 8256 | 2.829 | 2895.62 | 1.019 | 62.82 | 3.848 | 2145.60 |
| 4096 | 32 | 4 | 16512 | 5.656 | 2896.96 | 1.528 | 83.79 | 7.183 | 2298.71 |
| 4096 | 32 | 8 | 33024 | 11.338 | 2890.02 | 2.127 | 120.36 | 13.465 | 2452.53 |
| 4096 | 32 | 16 | 66048 | 22.709 | 2885.96 | 3.104 | 164.97 | 25.812 | 2558.79 |
| 4096 | 32 | 32 | 132096 | 45.301 | 2893.35 | 4.723 | 216.80 | 50.024 | 2640.63 |
| 8192 | 32 | 1 | 8224 | 3.022 | 2711.09 | 0.678 | 47.20 | 3.700 | 2222.89 |
| 8192 | 32 | 2 | 16448 | 6.039 | 2713.01 | 1.149 | 55.70 | 7.188 | 2288.21 |
| 8192 | 32 | 4 | 32896 | 12.050 | 2719.35 | 1.785 | 71.69 | 13.835 | 2377.67 |
| 8192 | 32 | 8 | 65792 | 24.113 | 2717.90 | 2.629 | 97.39 | 26.741 | 2460.31 |
| 8192 | 32 | 16 | 131584 | 48.178 | 2720.58 | 4.099 | 124.91 | 52.277 | 2517.06 |
| 8192 | 32 | 32 | 263168 | 96.401 | 2719.31 | 6.696 | 152.93 | 103.097 | 2552.63 |
- `llama-bench`
| model | size | params | backend | ngl | n_ubatch | fa | mmap | dio | test | t/s |
| ------------------------------ | ---------: | ---------: | ---------- | --: | -------: | -: | ---: | --: | --------------: | -------------------: |
| qwen3moe 30B.A3B Q8_0 | 30.25 GiB | 30.53 B | CUDA | 99 | 2048 | 1 | 0 | 1 | pp2048 | 2986.97 ± 18.87 |
| qwen3moe 30B.A3B Q8_0 | 30.25 GiB | 30.53 B | CUDA | 99 | 2048 | 1 | 0 | 1 | tg32 | 61.06 ± 0.23 |
| qwen3moe 30B.A3B Q8_0 | 30.25 GiB | 30.53 B | CUDA | 99 | 2048 | 1 | 0 | 1 | pp2048 @ d4096 | 2633.45 ± 6.26 |
| qwen3moe 30B.A3B Q8_0 | 30.25 GiB | 30.53 B | CUDA | 99 | 2048 | 1 | 0 | 1 | tg32 @ d4096 | 54.77 ± 0.28 |
| qwen3moe 30B.A3B Q8_0 | 30.25 GiB | 30.53 B | CUDA | 99 | 2048 | 1 | 0 | 1 | pp2048 @ d8192 | 2354.14 ± 3.84 |
| qwen3moe 30B.A3B Q8_0 | 30.25 GiB | 30.53 B | CUDA | 99 | 2048 | 1 | 0 | 1 | tg32 @ d8192 | 48.02 ± 0.40 |
| qwen3moe 30B.A3B Q8_0 | 30.25 GiB | 30.53 B | CUDA | 99 | 2048 | 1 | 0 | 1 | pp2048 @ d16384 | 1908.86 ± 4.25 |
| qwen3moe 30B.A3B Q8_0 | 30.25 GiB | 30.53 B | CUDA | 99 | 2048 | 1 | 0 | 1 | tg32 @ d16384 | 40.23 ± 0.10 |
| qwen3moe 30B.A3B Q8_0 | 30.25 GiB | 30.53 B | CUDA | 99 | 2048 | 1 | 0 | 1 | pp2048 @ d32768 | 1348.17 ± 2.00 |
| qwen3moe 30B.A3B Q8_0 | 30.25 GiB | 30.53 B | CUDA | 99 | 2048 | 1 | 0 | 1 | tg32 @ d32768 | 30.21 ± 0.04 |
build: 11fb327bf (7941)
## ggml-org/Qwen2.5-Coder-7B-Q8_0-GGUF
Model: https://huggingface.co/ggml-org/Qwen2.5-Coder-7B-Q8_0-GGUF
- `llama-batched-bench`
main: n_kv_max = 270336, n_batch = 2048, n_ubatch = 2048, flash_attn = 1, is_pp_shared = 0, is_tg_separate = 0, n_gpu_layers = -1, n_threads = 20, n_threads_batch = 20
| PP | TG | B | N_KV | T_PP s | S_PP t/s | T_TG s | S_TG t/s | T s | S t/s |
|-------|--------|------|--------|----------|----------|----------|----------|----------|----------|
| 512 | 32 | 1 | 544 | 0.212 | 2420.12 | 1.100 | 29.10 | 1.311 | 414.85 |
| 512 | 32 | 2 | 1088 | 0.428 | 2393.89 | 1.185 | 54.00 | 1.613 | 674.56 |
| 512 | 32 | 4 | 2176 | 0.894 | 2290.41 | 1.229 | 104.17 | 2.123 | 1025.02 |
| 512 | 32 | 8 | 4352 | 1.758 | 2330.36 | 1.319 | 194.15 | 3.076 | 1414.70 |
| 512 | 32 | 16 | 8704 | 3.508 | 2335.21 | 1.543 | 331.90 | 5.051 | 1723.33 |
| 512 | 32 | 32 | 17408 | 7.035 | 2328.93 | 1.738 | 589.21 | 8.773 | 1984.29 |
| 4096 | 32 | 1 | 4128 | 1.831 | 2237.25 | 1.125 | 28.44 | 2.956 | 1396.42 |
| 4096 | 32 | 2 | 8256 | 3.642 | 2249.48 | 1.253 | 51.07 | 4.895 | 1686.64 |
| 4096 | 32 | 4 | 16512 | 7.274 | 2252.26 | 1.380 | 92.72 | 8.655 | 1907.81 |
| 4096 | 32 | 8 | 33024 | 14.576 | 2248.09 | 1.617 | 158.29 | 16.193 | 2039.37 |
| 4096 | 32 | 16 | 66048 | 29.138 | 2249.17 | 2.081 | 246.01 | 31.219 | 2115.63 |
| 4096 | 32 | 32 | 132096 | 58.275 | 2249.19 | 2.814 | 363.87 | 61.089 | 2162.34 |
| 8192 | 32 | 1 | 8224 | 3.757 | 2180.26 | 1.184 | 27.03 | 4.941 | 1664.37 |
| 8192 | 32 | 2 | 16448 | 7.522 | 2178.05 | 1.341 | 47.73 | 8.863 | 1855.77 |
| 8192 | 32 | 4 | 32896 | 15.043 | 2178.25 | 1.548 | 82.69 | 16.591 | 1982.74 |
| 8192 | 32 | 8 | 65792 | 30.111 | 2176.49 | 1.937 | 132.13 | 32.048 | 2052.90 |
| 8192 | 32 | 16 | 131584 | 60.405 | 2169.90 | 2.706 | 189.21 | 63.111 | 2084.97 |
| 8192 | 32 | 32 | 263168 | 120.439 | 2176.58 | 3.993 | 256.46 | 124.432 | 2114.96 |
- `llama-bench`
| model | size | params | backend | ngl | n_ubatch | fa | mmap | dio | test | t/s |
| ------------------------------ | ---------: | ---------: | ---------- | --: | -------: | -: | ---: | --: | --------------: | -------------------: |
| qwen2 7B Q8_0 | 7.54 GiB | 7.62 B | CUDA | 99 | 2048 | 1 | 0 | 1 | pp2048 | 2250.28 ± 6.41 |
| qwen2 7B Q8_0 | 7.54 GiB | 7.62 B | CUDA | 99 | 2048 | 1 | 0 | 1 | tg32 | 29.43 ± 0.02 |
| qwen2 7B Q8_0 | 7.54 GiB | 7.62 B | CUDA | 99 | 2048 | 1 | 0 | 1 | pp2048 @ d4096 | 2100.19 ± 8.96 |
| qwen2 7B Q8_0 | 7.54 GiB | 7.62 B | CUDA | 99 | 2048 | 1 | 0 | 1 | tg32 @ d4096 | 28.61 ± 0.02 |
| qwen2 7B Q8_0 | 7.54 GiB | 7.62 B | CUDA | 99 | 2048 | 1 | 0 | 1 | pp2048 @ d8192 | 2007.56 ± 4.16 |
| qwen2 7B Q8_0 | 7.54 GiB | 7.62 B | CUDA | 99 | 2048 | 1 | 0 | 1 | tg32 @ d8192 | 27.38 ± 0.09 |
| qwen2 7B Q8_0 | 7.54 GiB | 7.62 B | CUDA | 99 | 2048 | 1 | 0 | 1 | pp2048 @ d16384 | 1779.11 ± 6.42 |
| qwen2 7B Q8_0 | 7.54 GiB | 7.62 B | CUDA | 99 | 2048 | 1 | 0 | 1 | tg32 @ d16384 | 25.72 ± 0.03 |
| qwen2 7B Q8_0 | 7.54 GiB | 7.62 B | CUDA | 99 | 2048 | 1 | 0 | 1 | pp2048 @ d32768 | 1471.23 ± 1.71 |
| qwen2 7B Q8_0 | 7.54 GiB | 7.62 B | CUDA | 99 | 2048 | 1 | 0 | 1 | tg32 @ d32768 | 22.51 ± 0.02 |
build: 11fb327bf (7941)
## ggml-org/gemma-3-4b-it-qat-GGUF
Model: https://huggingface.co/ggml-org/gemma-3-4b-it-qat-GGUF
- `llama-batched-bench`
main: n_kv_max = 270336, n_batch = 2048, n_ubatch = 2048, flash_attn = 1, is_pp_shared = 0, is_tg_separate = 0, n_gpu_layers = -1, n_threads = 20, n_threads_batch = 20
| PP | TG | B | N_KV | T_PP s | S_PP t/s | T_TG s | S_TG t/s | T s | S t/s |
|-------|--------|------|--------|----------|----------|----------|----------|----------|----------|
| 512 | 32 | 1 | 544 | 0.092 | 5566.97 | 0.412 | 77.63 | 0.504 | 1078.95 |
| 512 | 32 | 2 | 1088 | 0.161 | 6345.67 | 0.522 | 122.70 | 0.683 | 1593.06 |
| 512 | 32 | 4 | 2176 | 0.325 | 6309.87 | 0.562 | 227.68 | 0.887 | 2453.87 |
| 512 | 32 | 8 | 4352 | 0.643 | 6374.42 | 0.685 | 373.67 | 1.328 | 3277.94 |
| 512 | 32 | 16 | 8704 | 1.277 | 6413.64 | 0.915 | 559.47 | 2.192 | 3970.01 |
| 512 | 32 | 32 | 17408 | 2.518 | 6506.57 | 1.249 | 819.61 | 3.767 | 4620.64 |
| 4096 | 32 | 1 | 4128 | 0.674 | 6079.68 | 0.453 | 70.60 | 1.127 | 3662.88 |
| 4096 | 32 | 2 | 8256 | 1.335 | 6137.82 | 0.627 | 102.03 | 1.962 | 4208.11 |
| 4096 | 32 | 4 | 16512 | 2.657 | 6167.35 | 0.749 | 170.92 | 3.405 | 4848.71 |
| 4096 | 32 | 8 | 33024 | 5.307 | 6173.91 | 0.974 | 262.89 | 6.281 | 5257.53 |
| 4096 | 32 | 16 | 66048 | 10.610 | 6176.96 | 1.379 | 371.42 | 11.988 | 5509.40 |
| 4096 | 32 | 32 | 132096 | 21.213 | 6178.89 | 2.122 | 482.50 | 23.335 | 5660.82 |
| 8192 | 32 | 1 | 8224 | 1.359 | 6027.34 | 0.467 | 68.52 | 1.826 | 4503.48 |
| 8192 | 32 | 2 | 16448 | 2.699 | 6069.68 | 0.653 | 98.03 | 3.352 | 4906.68 |
| 8192 | 32 | 4 | 32896 | 5.366 | 6106.74 | 0.818 | 156.55 | 6.184 | 5319.96 |
| 8192 | 32 | 8 | 65792 | 10.755 | 6093.50 | 1.174 | 218.04 | 11.929 | 5515.22 |
| 8192 | 32 | 16 | 131584 | 21.484 | 6100.82 | 1.829 | 279.90 | 23.314 | 5644.11 |
| 8192 | 32 | 32 | 263168 | 42.950 | 6103.40 | 3.058 | 334.91 | 46.008 | 5720.05 |
- `llama-bench`
| model | size | params | backend | ngl | n_ubatch | fa | mmap | dio | test | t/s |
| ------------------------------ | ---------: | ---------: | ---------- | --: | -------: | -: | ---: | --: | --------------: | -------------------: |
| gemma3 4B Q4_0 | 2.35 GiB | 3.88 B | CUDA | 99 | 2048 | 1 | 0 | 1 | pp2048 | 5948.74 ± 10.61 |
| gemma3 4B Q4_0 | 2.35 GiB | 3.88 B | CUDA | 99 | 2048 | 1 | 0 | 1 | tg32 | 81.05 ± 0.20 |
| gemma3 4B Q4_0 | 2.35 GiB | 3.88 B | CUDA | 99 | 2048 | 1 | 0 | 1 | pp2048 @ d4096 | 5652.69 ± 34.29 |
| gemma3 4B Q4_0 | 2.35 GiB | 3.88 B | CUDA | 99 | 2048 | 1 | 0 | 1 | tg32 @ d4096 | 76.37 ± 0.58 |
| gemma3 4B Q4_0 | 2.35 GiB | 3.88 B | CUDA | 99 | 2048 | 1 | 0 | 1 | pp2048 @ d8192 | 5509.57 ± 40.69 |
| gemma3 4B Q4_0 | 2.35 GiB | 3.88 B | CUDA | 99 | 2048 | 1 | 0 | 1 | tg32 @ d8192 | 71.61 ± 0.80 |
| gemma3 4B Q4_0 | 2.35 GiB | 3.88 B | CUDA | 99 | 2048 | 1 | 0 | 1 | pp2048 @ d16384 | 5340.86 ± 36.92 |
| gemma3 4B Q4_0 | 2.35 GiB | 3.88 B | CUDA | 99 | 2048 | 1 | 0 | 1 | tg32 @ d16384 | 70.89 ± 0.34 |
| gemma3 4B Q4_0 | 2.35 GiB | 3.88 B | CUDA | 99 | 2048 | 1 | 0 | 1 | pp2048 @ d32768 | 5023.30 ± 13.52 |
| gemma3 4B Q4_0 | 2.35 GiB | 3.88 B | CUDA | 99 | 2048 | 1 | 0 | 1 | tg32 @ d32768 | 62.28 ± 0.30 |
build: 11fb327bf (7941)
## ggml-org/GLM-4.7-Flash-GGUF
Model: https://huggingface.co/ggml-org/GLM-4.7-Flash-GGUF
- `llama-batched-bench`
main: n_kv_max = 270336, n_batch = 2048, n_ubatch = 2048, flash_attn = 1, is_pp_shared = 0, is_tg_separate = 0, n_gpu_layers = -1, n_threads = 20, n_threads_batch = 20
| PP | TG | B | N_KV | T_PP s | S_PP t/s | T_TG s | S_TG t/s | T s | S t/s |
|-------|--------|------|--------|----------|----------|----------|----------|----------|----------|
| 512 | 32 | 1 | 544 | 0.433 | 1181.83 | 0.693 | 46.16 | 1.126 | 482.94 |
| 512 | 32 | 2 | 1088 | 0.439 | 2334.46 | 1.034 | 61.89 | 1.473 | 738.75 |
| 512 | 32 | 4 | 2176 | 0.772 | 2654.46 | 1.459 | 87.76 | 2.230 | 975.77 |
| 512 | 32 | 8 | 4352 | 1.541 | 2658.78 | 2.043 | 125.31 | 3.583 | 1214.47 |
| 512 | 32 | 16 | 8704 | 3.083 | 2656.91 | 2.675 | 191.42 | 5.758 | 1511.62 |
| 512 | 32 | 32 | 17408 | 6.159 | 2660.12 | 3.615 | 283.24 | 9.774 | 1780.98 |
| 4096 | 32 | 1 | 4128 | 1.915 | 2139.30 | 0.725 | 44.14 | 2.640 | 1563.83 |
| 4096 | 32 | 2 | 8256 | 3.834 | 2136.40 | 1.119 | 57.21 | 4.953 | 1666.81 |
| 4096 | 32 | 4 | 16512 | 7.636 | 2145.72 | 1.631 | 78.49 | 9.266 | 1781.93 |
| 4096 | 32 | 8 | 33024 | 15.295 | 2142.40 | 2.344 | 109.21 | 17.639 | 1872.20 |
| 4096 | 32 | 16 | 66048 | 30.573 | 2143.62 | 3.773 | 135.70 | 34.346 | 1923.04 |
| 4096 | 32 | 32 | 132096 | 61.282 | 2138.82 | 5.795 | 176.71 | 67.077 | 1969.31 |
| 8192 | 32 | 1 | 8224 | 4.510 | 1816.24 | 0.760 | 42.11 | 5.270 | 1560.44 |
| 8192 | 32 | 2 | 16448 | 9.036 | 1813.19 | 1.206 | 53.06 | 10.242 | 1605.91 |
| 8192 | 32 | 4 | 32896 | 18.070 | 1813.43 | 1.783 | 71.80 | 19.852 | 1657.03 |
| 8192 | 32 | 8 | 65792 | 36.125 | 1814.15 | 2.635 | 97.14 | 38.760 | 1697.41 |
| 8192 | 32 | 16 | 131584 | 72.367 | 1811.20 | 4.954 | 103.34 | 77.322 | 1701.77 |
| 8192 | 32 | 32 | 263168 | 144.501 | 1814.13 | 8.103 | 126.37 | 152.604 | 1724.51 |
- `llama-bench`
| model | size | params | backend | ngl | n_ubatch | fa | dio | test | t/s |
| ------------------------------ | ---------: | ---------: | ---------- | --: | -------: | -: | --: | --------------: | -------------------: |
| deepseek2 30B.A3B Q8_0 | 29.65 GiB | 29.94 B | CUDA | 99 | 2048 | 1 | 1 | pp2048 | 2364.18 ± 11.43 |
| deepseek2 30B.A3B Q8_0 | 29.65 GiB | 29.94 B | CUDA | 99 | 2048 | 1 | 1 | tg32 | 48.68 ± 0.12 |
| deepseek2 30B.A3B Q8_0 | 29.65 GiB | 29.94 B | CUDA | 99 | 2048 | 1 | 1 | pp2048 @ d4096 | 1684.13 ± 1.24 |
| deepseek2 30B.A3B Q8_0 | 29.65 GiB | 29.94 B | CUDA | 99 | 2048 | 1 | 1 | tg32 @ d4096 | 44.62 ± 0.22 |
| deepseek2 30B.A3B Q8_0 | 29.65 GiB | 29.94 B | CUDA | 99 | 2048 | 1 | 1 | pp2048 @ d8192 | 1314.68 ± 1.41 |
| deepseek2 30B.A3B Q8_0 | 29.65 GiB | 29.94 B | CUDA | 99 | 2048 | 1 | 1 | tg32 @ d8192 | 42.59 ± 0.11 |
| deepseek2 30B.A3B Q8_0 | 29.65 GiB | 29.94 B | CUDA | 99 | 2048 | 1 | 1 | pp2048 @ d16384 | 914.05 ± 3.32 |
| deepseek2 30B.A3B Q8_0 | 29.65 GiB | 29.94 B | CUDA | 99 | 2048 | 1 | 1 | tg32 @ d16384 | 38.72 ± 0.13 |
| deepseek2 30B.A3B Q8_0 | 29.65 GiB | 29.94 B | CUDA | 99 | 2048 | 1 | 1 | pp2048 @ d32768 | 567.20 ± 0.90 |
| deepseek2 30B.A3B Q8_0 | 29.65 GiB | 29.94 B | CUDA | 99 | 2048 | 1 | 1 | tg32 @ d32768 | 32.65 ± 0.09 |
build: 11fb327bf (7941)

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## System info
```bash
uname -a
Darwin gg-studio 25.2.0 Darwin Kernel Version 25.2.0: Tue Nov 18 21:07:05 PST 2025; root:xnu-12377.61.12~1/RELEASE_ARM64_T6020 arm64
g++ --version
Apple clang version 17.0.0 (clang-1700.3.19.1)
Target: arm64-apple-darwin25.2.0
```
## ggml-org/gpt-oss-20b-GGUF
Model: https://huggingface.co/ggml-org/gpt-oss-20b-GGUF
- `llama-batched-bench`
main: n_kv_max = 270336, n_batch = 2048, n_ubatch = 2048, flash_attn = 1, is_pp_shared = 0, is_tg_separate = 0, n_gpu_layers = -1, n_threads = 16, n_threads_batch = 16
| PP | TG | B | N_KV | T_PP s | S_PP t/s | T_TG s | S_TG t/s | T s | S t/s |
|-------|--------|------|--------|----------|----------|----------|----------|----------|----------|
| 512 | 32 | 1 | 544 | 0.215 | 2381.35 | 0.245 | 130.45 | 0.460 | 1181.81 |
| 512 | 32 | 2 | 1088 | 0.379 | 2701.43 | 0.382 | 167.56 | 0.761 | 1429.67 |
| 512 | 32 | 4 | 2176 | 0.721 | 2839.27 | 0.604 | 211.76 | 1.326 | 1641.32 |
| 512 | 32 | 8 | 4352 | 1.433 | 2858.30 | 1.033 | 247.75 | 2.466 | 1764.57 |
| 512 | 32 | 16 | 8704 | 2.853 | 2871.12 | 1.570 | 326.11 | 4.423 | 1967.77 |
| 512 | 32 | 32 | 17408 | 5.699 | 2874.95 | 1.910 | 536.15 | 7.609 | 2287.88 |
| 4096 | 32 | 1 | 4128 | 1.552 | 2638.56 | 0.334 | 95.72 | 1.887 | 2188.00 |
| 4096 | 32 | 2 | 8256 | 3.084 | 2655.88 | 0.404 | 158.54 | 3.488 | 2366.86 |
| 4096 | 32 | 4 | 16512 | 6.151 | 2663.78 | 0.652 | 196.39 | 6.802 | 2427.37 |
| 4096 | 32 | 8 | 33024 | 12.288 | 2666.77 | 1.135 | 225.47 | 13.423 | 2460.27 |
| 4096 | 32 | 16 | 66048 | 24.563 | 2668.12 | 1.762 | 290.55 | 26.325 | 2508.97 |
| 4096 | 32 | 32 | 132096 | 49.114 | 2668.73 | 2.398 | 426.94 | 51.512 | 2564.35 |
| 8192 | 32 | 1 | 8224 | 3.345 | 2448.78 | 0.275 | 116.46 | 3.620 | 2271.76 |
| 8192 | 32 | 2 | 16448 | 6.665 | 2458.11 | 0.425 | 150.71 | 7.090 | 2319.91 |
| 8192 | 32 | 4 | 32896 | 13.315 | 2460.92 | 0.691 | 185.21 | 14.006 | 2348.63 |
| 8192 | 32 | 8 | 65792 | 26.611 | 2462.73 | 1.212 | 211.16 | 27.823 | 2364.62 |
| 8192 | 32 | 16 | 131584 | 53.232 | 2462.27 | 1.919 | 266.83 | 55.151 | 2385.88 |
| 8192 | 32 | 32 | 263168 | 110.455 | 2373.30 | 2.752 | 372.03 | 113.208 | 2324.64 |
- `llama-bench`
| model | size | params | backend | threads | n_ubatch | fa | test | t/s |
| ------------------------------ | ---------: | ---------: | ---------- | ------: | -------: | -: | --------------: | -------------------: |
| gpt-oss 20B MXFP4 MoE | 11.27 GiB | 20.91 B | MTL,BLAS | 16 | 2048 | 1 | pp2048 | 2713.40 ± 3.56 |
| gpt-oss 20B MXFP4 MoE | 11.27 GiB | 20.91 B | MTL,BLAS | 16 | 2048 | 1 | tg32 | 129.97 ± 3.90 |
| gpt-oss 20B MXFP4 MoE | 11.27 GiB | 20.91 B | MTL,BLAS | 16 | 2048 | 1 | pp2048 @ d4096 | 2324.59 ± 3.01 |
| gpt-oss 20B MXFP4 MoE | 11.27 GiB | 20.91 B | MTL,BLAS | 16 | 2048 | 1 | tg32 @ d4096 | 123.38 ± 0.17 |
| gpt-oss 20B MXFP4 MoE | 11.27 GiB | 20.91 B | MTL,BLAS | 16 | 2048 | 1 | pp2048 @ d8192 | 1989.82 ± 30.11 |
| gpt-oss 20B MXFP4 MoE | 11.27 GiB | 20.91 B | MTL,BLAS | 16 | 2048 | 1 | tg32 @ d8192 | 117.39 ± 0.33 |
| gpt-oss 20B MXFP4 MoE | 11.27 GiB | 20.91 B | MTL,BLAS | 16 | 2048 | 1 | pp2048 @ d16384 | 1556.54 ± 6.22 |
| gpt-oss 20B MXFP4 MoE | 11.27 GiB | 20.91 B | MTL,BLAS | 16 | 2048 | 1 | tg32 @ d16384 | 109.75 ± 0.42 |
| gpt-oss 20B MXFP4 MoE | 11.27 GiB | 20.91 B | MTL,BLAS | 16 | 2048 | 1 | pp2048 @ d32768 | 1122.63 ± 1.45 |
| gpt-oss 20B MXFP4 MoE | 11.27 GiB | 20.91 B | MTL,BLAS | 16 | 2048 | 1 | tg32 @ d32768 | 98.25 ± 0.08 |
build: b828e18c7 (7948)
## ggml-org/gpt-oss-120b-GGUF
Model: https://huggingface.co/ggml-org/gpt-oss-120b-GGUF
- `llama-batched-bench`
main: n_kv_max = 270336, n_batch = 2048, n_ubatch = 2048, flash_attn = 1, is_pp_shared = 0, is_tg_separate = 0, n_gpu_layers = -1, n_threads = 16, n_threads_batch = 16
| PP | TG | B | N_KV | T_PP s | S_PP t/s | T_TG s | S_TG t/s | T s | S t/s |
|-------|--------|------|--------|----------|----------|----------|----------|----------|----------|
| 512 | 32 | 1 | 544 | 0.426 | 1200.92 | 0.361 | 88.56 | 0.788 | 690.64 |
| 512 | 32 | 2 | 1088 | 0.683 | 1500.14 | 0.545 | 117.35 | 1.228 | 886.02 |
| 512 | 32 | 4 | 2176 | 1.204 | 1701.56 | 0.847 | 151.19 | 2.050 | 1061.34 |
| 512 | 32 | 8 | 4352 | 2.402 | 1705.20 | 1.455 | 176.00 | 3.857 | 1128.45 |
| 512 | 32 | 16 | 8704 | 4.802 | 1705.90 | 2.349 | 217.93 | 7.152 | 1217.08 |
| 512 | 32 | 32 | 17408 | 9.593 | 1707.85 | 3.665 | 279.42 | 13.258 | 1313.01 |
| 4096 | 32 | 1 | 4128 | 2.581 | 1587.08 | 0.390 | 82.12 | 2.970 | 1389.67 |
| 4096 | 32 | 2 | 8256 | 5.124 | 1598.79 | 0.589 | 108.62 | 5.713 | 1445.10 |
| 4096 | 32 | 4 | 16512 | 10.231 | 1601.47 | 0.928 | 137.98 | 11.158 | 1479.80 |
| 4096 | 32 | 8 | 33024 | 20.468 | 1600.94 | 1.606 | 159.38 | 22.074 | 1496.04 |
| 4096 | 32 | 16 | 66048 | 40.924 | 1601.42 | 2.639 | 193.99 | 43.563 | 1516.15 |
| 4096 | 32 | 32 | 132096 | 81.819 | 1601.98 | 4.466 | 229.29 | 86.284 | 1530.94 |
| 8192 | 32 | 1 | 8224 | 5.517 | 1484.74 | 0.409 | 78.16 | 5.927 | 1387.58 |
| 8192 | 32 | 2 | 16448 | 11.008 | 1488.43 | 0.622 | 102.92 | 11.629 | 1414.34 |
| 8192 | 32 | 4 | 32896 | 22.002 | 1489.29 | 0.987 | 129.66 | 22.990 | 1430.90 |
| 8192 | 32 | 8 | 65792 | 46.051 | 1423.11 | 1.858 | 137.79 | 47.909 | 1373.27 |
| 8192 | 32 | 16 | 131584 | 97.680 | 1341.85 | 2.872 | 178.28 | 100.552 | 1308.62 |
| 8192 | 32 | 32 | 263168 | 176.407 | 1486.02 | 5.048 | 202.85 | 181.455 | 1450.32 |
- `llama-bench`
| model | size | params | backend | threads | n_ubatch | fa | test | t/s |
| ------------------------------ | ---------: | ---------: | ---------- | ------: | -------: | -: | --------------: | -------------------: |
| gpt-oss 120B MXFP4 MoE | 59.02 GiB | 116.83 B | MTL,BLAS | 16 | 2048 | 1 | pp2048 | 1648.69 ± 1.80 |
| gpt-oss 120B MXFP4 MoE | 59.02 GiB | 116.83 B | MTL,BLAS | 16 | 2048 | 1 | tg32 | 85.60 ± 0.52 |
| gpt-oss 120B MXFP4 MoE | 59.02 GiB | 116.83 B | MTL,BLAS | 16 | 2048 | 1 | pp2048 @ d4096 | 1429.86 ± 1.01 |
| gpt-oss 120B MXFP4 MoE | 59.02 GiB | 116.83 B | MTL,BLAS | 16 | 2048 | 1 | tg32 @ d4096 | 82.03 ± 0.12 |
| gpt-oss 120B MXFP4 MoE | 59.02 GiB | 116.83 B | MTL,BLAS | 16 | 2048 | 1 | pp2048 @ d8192 | 1257.90 ± 1.81 |
| gpt-oss 120B MXFP4 MoE | 59.02 GiB | 116.83 B | MTL,BLAS | 16 | 2048 | 1 | tg32 @ d8192 | 78.23 ± 0.33 |
| gpt-oss 120B MXFP4 MoE | 59.02 GiB | 116.83 B | MTL,BLAS | 16 | 2048 | 1 | pp2048 @ d16384 | 1013.49 ± 0.70 |
| gpt-oss 120B MXFP4 MoE | 59.02 GiB | 116.83 B | MTL,BLAS | 16 | 2048 | 1 | tg32 @ d16384 | 73.20 ± 0.28 |
| gpt-oss 120B MXFP4 MoE | 59.02 GiB | 116.83 B | MTL,BLAS | 16 | 2048 | 1 | pp2048 @ d32768 | 721.11 ± 0.58 |
| gpt-oss 120B MXFP4 MoE | 59.02 GiB | 116.83 B | MTL,BLAS | 16 | 2048 | 1 | tg32 @ d32768 | 65.52 ± 0.10 |
build: b828e18c7 (7948)
## ggml-org/Qwen3-Coder-30B-A3B-Instruct-Q8_0-GGUF
Model: https://huggingface.co/ggml-org/Qwen3-Coder-30B-A3B-Instruct-Q8_0-GGUF
- `llama-batched-bench`
main: n_kv_max = 270336, n_batch = 2048, n_ubatch = 2048, flash_attn = 1, is_pp_shared = 0, is_tg_separate = 0, n_gpu_layers = -1, n_threads = 16, n_threads_batch = 16
| PP | TG | B | N_KV | T_PP s | S_PP t/s | T_TG s | S_TG t/s | T s | S t/s |
|-------|--------|------|--------|----------|----------|----------|----------|----------|----------|
| 512 | 32 | 1 | 544 | 0.243 | 2109.23 | 0.419 | 76.34 | 0.662 | 821.84 |
| 512 | 32 | 2 | 1088 | 0.406 | 2521.40 | 0.575 | 111.36 | 0.981 | 1109.27 |
| 512 | 32 | 4 | 2176 | 0.744 | 2751.65 | 0.841 | 152.22 | 1.585 | 1372.71 |
| 512 | 32 | 8 | 4352 | 1.479 | 2770.20 | 1.330 | 192.48 | 2.809 | 1549.53 |
| 512 | 32 | 16 | 8704 | 2.951 | 2776.20 | 2.572 | 199.05 | 5.523 | 1575.93 |
| 512 | 32 | 32 | 17408 | 5.899 | 2777.64 | 2.603 | 393.34 | 8.502 | 2047.54 |
| 4096 | 32 | 1 | 4128 | 1.901 | 2154.15 | 0.474 | 67.58 | 2.375 | 1738.14 |
| 4096 | 32 | 2 | 8256 | 3.788 | 2162.89 | 0.652 | 98.17 | 4.439 | 1859.69 |
| 4096 | 32 | 4 | 16512 | 7.564 | 2166.18 | 0.990 | 129.24 | 8.554 | 1930.34 |
| 4096 | 32 | 8 | 33024 | 15.121 | 2166.98 | 1.632 | 156.82 | 16.754 | 1971.12 |
| 4096 | 32 | 16 | 66048 | 30.241 | 2167.09 | 3.166 | 161.72 | 33.407 | 1977.04 |
| 4096 | 32 | 32 | 132096 | 60.474 | 2167.42 | 3.780 | 270.93 | 64.254 | 2055.86 |
| 8192 | 32 | 1 | 8224 | 4.733 | 1730.92 | 0.483 | 66.29 | 5.215 | 1576.85 |
| 8192 | 32 | 2 | 16448 | 9.459 | 1732.09 | 0.722 | 88.58 | 10.182 | 1615.46 |
| 8192 | 32 | 4 | 32896 | 18.912 | 1732.65 | 1.120 | 114.26 | 20.032 | 1642.14 |
| 8192 | 32 | 8 | 65792 | 37.797 | 1733.91 | 1.873 | 136.67 | 39.670 | 1658.49 |
| 8192 | 32 | 16 | 131584 | 84.133 | 1557.92 | 3.718 | 137.72 | 87.850 | 1497.82 |
| 8192 | 32 | 32 | 263168 | 157.550 | 1663.88 | 4.854 | 210.98 | 162.403 | 1620.46 |
- `llama-bench`
| model | size | params | backend | threads | n_ubatch | fa | test | t/s |
| ------------------------------ | ---------: | ---------: | ---------- | ------: | -------: | -: | --------------: | -------------------: |
| qwen3moe 30B.A3B Q8_0 | 30.25 GiB | 30.53 B | MTL,BLAS | 16 | 2048 | 1 | pp2048 | 2453.11 ± 1.70 |
| qwen3moe 30B.A3B Q8_0 | 30.25 GiB | 30.53 B | MTL,BLAS | 16 | 2048 | 1 | tg32 | 78.97 ± 0.46 |
| qwen3moe 30B.A3B Q8_0 | 30.25 GiB | 30.53 B | MTL,BLAS | 16 | 2048 | 1 | pp2048 @ d4096 | 1569.46 ± 1.97 |
| qwen3moe 30B.A3B Q8_0 | 30.25 GiB | 30.53 B | MTL,BLAS | 16 | 2048 | 1 | tg32 @ d4096 | 71.18 ± 0.37 |
| qwen3moe 30B.A3B Q8_0 | 30.25 GiB | 30.53 B | MTL,BLAS | 16 | 2048 | 1 | pp2048 @ d8192 | 1145.51 ± 1.16 |
| qwen3moe 30B.A3B Q8_0 | 30.25 GiB | 30.53 B | MTL,BLAS | 16 | 2048 | 1 | tg32 @ d8192 | 65.11 ± 0.36 |
| qwen3moe 30B.A3B Q8_0 | 30.25 GiB | 30.53 B | MTL,BLAS | 16 | 2048 | 1 | pp2048 @ d16384 | 741.04 ± 0.74 |
| qwen3moe 30B.A3B Q8_0 | 30.25 GiB | 30.53 B | MTL,BLAS | 16 | 2048 | 1 | tg32 @ d16384 | 56.87 ± 0.14 |
| qwen3moe 30B.A3B Q8_0 | 30.25 GiB | 30.53 B | MTL,BLAS | 16 | 2048 | 1 | pp2048 @ d32768 | 431.31 ± 0.31 |
| qwen3moe 30B.A3B Q8_0 | 30.25 GiB | 30.53 B | MTL,BLAS | 16 | 2048 | 1 | tg32 @ d32768 | 45.26 ± 0.11 |
build: b828e18c7 (7948)
## ggml-org/Qwen2.5-Coder-7B-Q8_0-GGUF
Model: https://huggingface.co/ggml-org/Qwen2.5-Coder-7B-Q8_0-GGUF
- `llama-batched-bench`
main: n_kv_max = 270336, n_batch = 2048, n_ubatch = 2048, flash_attn = 1, is_pp_shared = 0, is_tg_separate = 0, n_gpu_layers = -1, n_threads = 16, n_threads_batch = 16
| PP | TG | B | N_KV | T_PP s | S_PP t/s | T_TG s | S_TG t/s | T s | S t/s |
|-------|--------|------|--------|----------|----------|----------|----------|----------|----------|
| 512 | 32 | 1 | 544 | 0.339 | 1509.22 | 0.409 | 78.17 | 0.749 | 726.67 |
| 512 | 32 | 2 | 1088 | 0.646 | 1584.93 | 0.483 | 132.45 | 1.129 | 963.45 |
| 512 | 32 | 4 | 2176 | 1.258 | 1627.50 | 0.585 | 218.67 | 1.844 | 1180.21 |
| 512 | 32 | 8 | 4352 | 2.506 | 1634.41 | 1.005 | 254.83 | 3.511 | 1239.64 |
| 512 | 32 | 16 | 8704 | 5.007 | 1635.99 | 1.595 | 321.07 | 6.602 | 1318.38 |
| 512 | 32 | 32 | 17408 | 10.007 | 1637.19 | 1.676 | 611.12 | 11.683 | 1490.03 |
| 4096 | 32 | 1 | 4128 | 2.730 | 1500.46 | 0.431 | 74.31 | 3.160 | 1306.12 |
| 4096 | 32 | 2 | 8256 | 5.446 | 1504.33 | 0.524 | 122.04 | 5.970 | 1382.91 |
| 4096 | 32 | 4 | 16512 | 10.875 | 1506.59 | 0.662 | 193.45 | 11.537 | 1431.28 |
| 4096 | 32 | 8 | 33024 | 21.749 | 1506.61 | 1.158 | 221.11 | 22.907 | 1441.64 |
| 4096 | 32 | 16 | 66048 | 43.477 | 1507.36 | 1.901 | 269.32 | 45.378 | 1455.49 |
| 4096 | 32 | 32 | 132096 | 86.954 | 1507.37 | 2.325 | 440.42 | 89.279 | 1479.59 |
| 8192 | 32 | 1 | 8224 | 5.940 | 1379.21 | 0.449 | 71.20 | 6.389 | 1287.20 |
| 8192 | 32 | 2 | 16448 | 11.865 | 1380.84 | 0.559 | 114.59 | 12.424 | 1323.92 |
| 8192 | 32 | 4 | 32896 | 23.723 | 1381.25 | 0.728 | 175.80 | 24.452 | 1345.35 |
| 8192 | 32 | 8 | 65792 | 47.434 | 1381.63 | 1.279 | 200.09 | 48.713 | 1350.60 |
| 8192 | 32 | 16 | 131584 | 94.864 | 1381.69 | 2.198 | 232.97 | 97.061 | 1355.68 |
| 8192 | 32 | 32 | 263168 | 189.743 | 1381.57 | 3.052 | 335.50 | 192.795 | 1365.01 |
- `llama-bench`
| model | size | params | backend | threads | n_ubatch | fa | test | t/s |
| ------------------------------ | ---------: | ---------: | ---------- | ------: | -------: | -: | --------------: | -------------------: |
| qwen2 7B Q8_0 | 7.54 GiB | 7.62 B | MTL,BLAS | 16 | 2048 | 1 | pp2048 | 1565.91 ± 0.86 |
| qwen2 7B Q8_0 | 7.54 GiB | 7.62 B | MTL,BLAS | 16 | 2048 | 1 | tg32 | 79.68 ± 0.39 |
| qwen2 7B Q8_0 | 7.54 GiB | 7.62 B | MTL,BLAS | 16 | 2048 | 1 | pp2048 @ d4096 | 1317.41 ± 1.02 |
| qwen2 7B Q8_0 | 7.54 GiB | 7.62 B | MTL,BLAS | 16 | 2048 | 1 | tg32 @ d4096 | 74.70 ± 0.04 |
| qwen2 7B Q8_0 | 7.54 GiB | 7.62 B | MTL,BLAS | 16 | 2048 | 1 | pp2048 @ d8192 | 1134.65 ± 0.76 |
| qwen2 7B Q8_0 | 7.54 GiB | 7.62 B | MTL,BLAS | 16 | 2048 | 1 | tg32 @ d8192 | 71.31 ± 0.12 |
| qwen2 7B Q8_0 | 7.54 GiB | 7.62 B | MTL,BLAS | 16 | 2048 | 1 | pp2048 @ d16384 | 886.46 ± 0.78 |
| qwen2 7B Q8_0 | 7.54 GiB | 7.62 B | MTL,BLAS | 16 | 2048 | 1 | tg32 @ d16384 | 65.93 ± 0.06 |
| qwen2 7B Q8_0 | 7.54 GiB | 7.62 B | MTL,BLAS | 16 | 2048 | 1 | pp2048 @ d32768 | 612.21 ± 0.30 |
| qwen2 7B Q8_0 | 7.54 GiB | 7.62 B | MTL,BLAS | 16 | 2048 | 1 | tg32 @ d32768 | 56.83 ± 0.02 |
build: b828e18c7 (7948)
## ggml-org/gemma-3-4b-it-qat-GGUF
Model: https://huggingface.co/ggml-org/gemma-3-4b-it-qat-GGUF
- `llama-batched-bench`
main: n_kv_max = 270336, n_batch = 2048, n_ubatch = 2048, flash_attn = 1, is_pp_shared = 0, is_tg_separate = 0, n_gpu_layers = -1, n_threads = 16, n_threads_batch = 16
| PP | TG | B | N_KV | T_PP s | S_PP t/s | T_TG s | S_TG t/s | T s | S t/s |
|-------|--------|------|--------|----------|----------|----------|----------|----------|----------|
| 512 | 32 | 1 | 544 | 0.186 | 2748.06 | 0.235 | 136.28 | 0.421 | 1291.78 |
| 512 | 32 | 2 | 1088 | 0.342 | 2990.95 | 0.312 | 204.99 | 0.655 | 1662.15 |
| 512 | 32 | 4 | 2176 | 0.662 | 3092.69 | 0.404 | 316.97 | 1.066 | 2041.21 |
| 512 | 32 | 8 | 4352 | 1.317 | 3110.41 | 0.579 | 441.80 | 1.896 | 2294.97 |
| 512 | 32 | 16 | 8704 | 2.625 | 3120.23 | 1.207 | 424.08 | 3.833 | 2270.93 |
| 512 | 32 | 32 | 17408 | 5.242 | 3125.34 | 1.299 | 788.23 | 6.541 | 2661.19 |
| 4096 | 32 | 1 | 4128 | 1.408 | 2909.90 | 0.296 | 108.07 | 1.704 | 2422.95 |
| 4096 | 32 | 2 | 8256 | 2.793 | 2933.40 | 0.325 | 197.00 | 3.118 | 2648.25 |
| 4096 | 32 | 4 | 16512 | 5.567 | 2943.22 | 0.440 | 291.07 | 6.006 | 2749.05 |
| 4096 | 32 | 8 | 33024 | 11.114 | 2948.23 | 0.640 | 400.26 | 11.754 | 2809.59 |
| 4096 | 32 | 16 | 66048 | 22.217 | 2949.76 | 1.327 | 385.83 | 23.544 | 2805.26 |
| 4096 | 32 | 32 | 132096 | 44.420 | 2950.77 | 1.553 | 659.30 | 45.973 | 2873.36 |
| 8192 | 32 | 1 | 8224 | 2.860 | 2864.58 | 0.250 | 127.90 | 3.110 | 2644.42 |
| 8192 | 32 | 2 | 16448 | 5.702 | 2873.63 | 0.335 | 191.07 | 6.036 | 2724.77 |
| 8192 | 32 | 4 | 32896 | 11.383 | 2878.69 | 0.456 | 280.72 | 11.839 | 2778.63 |
| 8192 | 32 | 8 | 65792 | 22.750 | 2880.75 | 0.671 | 381.48 | 23.421 | 2809.14 |
| 8192 | 32 | 16 | 131584 | 45.484 | 2881.74 | 1.406 | 364.04 | 46.890 | 2806.22 |
| 8192 | 32 | 32 | 263168 | 90.956 | 2882.10 | 1.793 | 570.98 | 92.749 | 2837.41 |
- `llama-bench`
| model | size | params | backend | threads | n_ubatch | fa | test | t/s |
| ------------------------------ | ---------: | ---------: | ---------- | ------: | -------: | -: | --------------: | -------------------: |
| gemma3 4B Q4_0 | 2.35 GiB | 3.88 B | MTL,BLAS | 16 | 2048 | 1 | pp2048 | 2923.59 ± 3.10 |
| gemma3 4B Q4_0 | 2.35 GiB | 3.88 B | MTL,BLAS | 16 | 2048 | 1 | tg32 | 134.28 ± 1.29 |
| gemma3 4B Q4_0 | 2.35 GiB | 3.88 B | MTL,BLAS | 16 | 2048 | 1 | pp2048 @ d4096 | 2748.21 ± 3.05 |
| gemma3 4B Q4_0 | 2.35 GiB | 3.88 B | MTL,BLAS | 16 | 2048 | 1 | tg32 @ d4096 | 133.11 ± 0.08 |
| gemma3 4B Q4_0 | 2.35 GiB | 3.88 B | MTL,BLAS | 16 | 2048 | 1 | pp2048 @ d8192 | 2641.45 ± 2.31 |
| gemma3 4B Q4_0 | 2.35 GiB | 3.88 B | MTL,BLAS | 16 | 2048 | 1 | tg32 @ d8192 | 125.85 ± 0.35 |
| gemma3 4B Q4_0 | 2.35 GiB | 3.88 B | MTL,BLAS | 16 | 2048 | 1 | pp2048 @ d16384 | 2446.20 ± 2.94 |
| gemma3 4B Q4_0 | 2.35 GiB | 3.88 B | MTL,BLAS | 16 | 2048 | 1 | tg32 @ d16384 | 125.00 ± 0.12 |
| gemma3 4B Q4_0 | 2.35 GiB | 3.88 B | MTL,BLAS | 16 | 2048 | 1 | pp2048 @ d32768 | 2129.18 ± 7.43 |
| gemma3 4B Q4_0 | 2.35 GiB | 3.88 B | MTL,BLAS | 16 | 2048 | 1 | tg32 @ d32768 | 113.14 ± 0.10 |
build: b828e18c7 (7948)
## ggml-org/GLM-4.7-Flash-GGUF
Model: https://huggingface.co/ggml-org/GLM-4.7-Flash-GGUF
- `llama-batched-bench`
main: n_kv_max = 270336, n_batch = 2048, n_ubatch = 2048, flash_attn = 1, is_pp_shared = 0, is_tg_separate = 0, n_gpu_layers = -1, n_threads = 16, n_threads_batch = 16
| PP | TG | B | N_KV | T_PP s | S_PP t/s | T_TG s | S_TG t/s | T s | S t/s |
|-------|--------|------|--------|----------|----------|----------|----------|----------|----------|
| 512 | 32 | 1 | 544 | 0.326 | 1568.69 | 0.522 | 61.28 | 0.849 | 641.09 |
| 512 | 32 | 2 | 1088 | 0.528 | 1939.42 | 0.744 | 86.07 | 1.272 | 855.63 |
| 512 | 32 | 4 | 2176 | 0.968 | 2114.85 | 1.105 | 115.85 | 2.073 | 1049.56 |
| 512 | 32 | 8 | 4352 | 1.928 | 2124.62 | 1.684 | 151.99 | 3.612 | 1204.82 |
| 512 | 32 | 16 | 8704 | 3.844 | 2131.34 | 3.141 | 162.99 | 6.985 | 1246.11 |
| 512 | 32 | 32 | 17408 | 7.683 | 2132.38 | 3.924 | 260.95 | 11.608 | 1499.71 |
| 4096 | 32 | 1 | 4128 | 3.280 | 1248.75 | 0.723 | 44.29 | 4.003 | 1031.33 |
| 4096 | 32 | 2 | 8256 | 6.545 | 1251.63 | 0.930 | 68.85 | 7.475 | 1104.53 |
| 4096 | 32 | 4 | 16512 | 13.080 | 1252.64 | 1.454 | 88.03 | 14.534 | 1136.12 |
| 4096 | 32 | 8 | 33024 | 26.154 | 1252.90 | 2.388 | 107.20 | 28.542 | 1157.04 |
| 4096 | 32 | 16 | 66048 | 52.297 | 1253.14 | 4.724 | 108.37 | 57.022 | 1158.30 |
| 4096 | 32 | 32 | 132096 | 104.578 | 1253.34 | 7.266 | 140.93 | 111.844 | 1181.08 |
| 8192 | 32 | 1 | 8224 | 9.623 | 851.31 | 0.767 | 41.72 | 10.390 | 791.54 |
| 8192 | 32 | 2 | 16448 | 20.916 | 783.32 | 1.148 | 55.74 | 22.064 | 745.45 |
| 8192 | 32 | 4 | 32896 | 43.509 | 753.14 | 1.833 | 69.82 | 45.342 | 725.51 |
| 8192 | 32 | 8 | 65792 | 79.621 | 823.10 | 3.180 | 80.50 | 82.801 | 794.58 |
| 8192 | 32 | 16 | 131584 | 153.770 | 852.39 | 6.502 | 78.74 | 160.272 | 821.00 |
| 8192 | 32 | 32 | 263168 | 307.539 | 852.39 | 10.839 | 94.48 | 318.378 | 826.59 |
- `llama-bench`
| model | size | params | backend | threads | n_ubatch | fa | test | t/s |
| ------------------------------ | ---------: | ---------: | ---------- | ------: | -------: | -: | --------------: | -------------------: |
| deepseek2 30B.A3B Q8_0 | 29.65 GiB | 29.94 B | MTL,BLAS | 16 | 2048 | 1 | pp2048 | 1629.33 ± 0.27 |
| deepseek2 30B.A3B Q8_0 | 29.65 GiB | 29.94 B | MTL,BLAS | 16 | 2048 | 1 | tg32 | 59.58 ± 0.13 |
| deepseek2 30B.A3B Q8_0 | 29.65 GiB | 29.94 B | MTL,BLAS | 16 | 2048 | 1 | pp2048 @ d4096 | 732.67 ± 0.42 |
| deepseek2 30B.A3B Q8_0 | 29.65 GiB | 29.94 B | MTL,BLAS | 16 | 2048 | 1 | tg32 @ d4096 | 47.44 ± 0.15 |
| deepseek2 30B.A3B Q8_0 | 29.65 GiB | 29.94 B | MTL,BLAS | 16 | 2048 | 1 | pp2048 @ d8192 | 474.33 ± 0.33 |
| deepseek2 30B.A3B Q8_0 | 29.65 GiB | 29.94 B | MTL,BLAS | 16 | 2048 | 1 | tg32 @ d8192 | 40.20 ± 0.20 |
| deepseek2 30B.A3B Q8_0 | 29.65 GiB | 29.94 B | MTL,BLAS | 16 | 2048 | 1 | pp2048 @ d16384 | 277.46 ± 0.09 |
| deepseek2 30B.A3B Q8_0 | 29.65 GiB | 29.94 B | MTL,BLAS | 16 | 2048 | 1 | tg32 @ d16384 | 31.50 ± 0.93 |
| deepseek2 30B.A3B Q8_0 | 29.65 GiB | 29.94 B | MTL,BLAS | 16 | 2048 | 1 | pp2048 @ d32768 | 151.44 ± 0.05 |
| deepseek2 30B.A3B Q8_0 | 29.65 GiB | 29.94 B | MTL,BLAS | 16 | 2048 | 1 | tg32 @ d32768 | 21.81 ± 0.01 |
build: b828e18c7 (7948)

View File

@ -1,4 +1,4 @@
#!/usr/bin/env bash
#!/bin/bash
#
# Options
IOS_MIN_OS_VERSION=16.4
@ -8,7 +8,6 @@ TVOS_MIN_OS_VERSION=16.4
BUILD_SHARED_LIBS=OFF
LLAMA_BUILD_EXAMPLES=OFF
LLAMA_BUILD_TOOLS=OFF
LLAMA_BUILD_TESTS=OFF
LLAMA_BUILD_SERVER=OFF
GGML_METAL=ON
@ -32,7 +31,6 @@ COMMON_CMAKE_ARGS=(
-DCMAKE_XCODE_ATTRIBUTE_DEVELOPMENT_TEAM=ggml
-DBUILD_SHARED_LIBS=${BUILD_SHARED_LIBS}
-DLLAMA_BUILD_EXAMPLES=${LLAMA_BUILD_EXAMPLES}
-DLLAMA_BUILD_TOOLS=${LLAMA_BUILD_TOOLS}
-DLLAMA_BUILD_TESTS=${LLAMA_BUILD_TESTS}
-DLLAMA_BUILD_SERVER=${LLAMA_BUILD_SERVER}
-DGGML_METAL_EMBED_LIBRARY=${GGML_METAL_EMBED_LIBRARY}
@ -117,7 +115,6 @@ setup_framework_structure() {
# Copy all required headers (common for all platforms)
cp include/llama.h ${header_path}
cp ggml/include/ggml.h ${header_path}
cp ggml/include/ggml-opt.h ${header_path}
cp ggml/include/ggml-alloc.h ${header_path}
cp ggml/include/ggml-backend.h ${header_path}
cp ggml/include/ggml-metal.h ${header_path}
@ -414,7 +411,7 @@ cmake -B build-ios-sim -G Xcode \
-DCMAKE_XCODE_ATTRIBUTE_SUPPORTED_PLATFORMS=iphonesimulator \
-DCMAKE_C_FLAGS="${COMMON_C_FLAGS}" \
-DCMAKE_CXX_FLAGS="${COMMON_CXX_FLAGS}" \
-DLLAMA_OPENSSL=OFF \
-DLLAMA_CURL=OFF \
-S .
cmake --build build-ios-sim --config Release -- -quiet
@ -422,13 +419,12 @@ echo "Building for iOS devices..."
cmake -B build-ios-device -G Xcode \
"${COMMON_CMAKE_ARGS[@]}" \
-DCMAKE_OSX_DEPLOYMENT_TARGET=${IOS_MIN_OS_VERSION} \
-DCMAKE_SYSTEM_NAME=iOS \
-DCMAKE_OSX_SYSROOT=iphoneos \
-DCMAKE_OSX_ARCHITECTURES="arm64" \
-DCMAKE_XCODE_ATTRIBUTE_SUPPORTED_PLATFORMS=iphoneos \
-DCMAKE_C_FLAGS="${COMMON_C_FLAGS}" \
-DCMAKE_CXX_FLAGS="${COMMON_CXX_FLAGS}" \
-DLLAMA_OPENSSL=OFF \
-DLLAMA_CURL=OFF \
-S .
cmake --build build-ios-device --config Release -- -quiet
@ -439,7 +435,7 @@ cmake -B build-macos -G Xcode \
-DCMAKE_OSX_ARCHITECTURES="arm64;x86_64" \
-DCMAKE_C_FLAGS="${COMMON_C_FLAGS}" \
-DCMAKE_CXX_FLAGS="${COMMON_CXX_FLAGS}" \
-DLLAMA_OPENSSL=OFF \
-DLLAMA_CURL=OFF \
-S .
cmake --build build-macos --config Release -- -quiet
@ -453,9 +449,7 @@ cmake -B build-visionos -G Xcode \
-DCMAKE_XCODE_ATTRIBUTE_SUPPORTED_PLATFORMS=xros \
-DCMAKE_C_FLAGS="-D_XOPEN_SOURCE=700 ${COMMON_C_FLAGS}" \
-DCMAKE_CXX_FLAGS="-D_XOPEN_SOURCE=700 ${COMMON_CXX_FLAGS}" \
-DLLAMA_OPENSSL=OFF \
-DLLAMA_HTTPLIB=OFF \
-DLLAMA_BUILD_SERVER=OFF \
-DLLAMA_CURL=OFF \
-S .
cmake --build build-visionos --config Release -- -quiet
@ -469,9 +463,7 @@ cmake -B build-visionos-sim -G Xcode \
-DCMAKE_XCODE_ATTRIBUTE_SUPPORTED_PLATFORMS=xrsimulator \
-DCMAKE_C_FLAGS="-D_XOPEN_SOURCE=700 ${COMMON_C_FLAGS}" \
-DCMAKE_CXX_FLAGS="-D_XOPEN_SOURCE=700 ${COMMON_CXX_FLAGS}" \
-DLLAMA_OPENSSL=OFF \
-DLLAMA_HTTPLIB=OFF \
-DLLAMA_BUILD_SERVER=OFF \
-DLLAMA_CURL=OFF \
-S .
cmake --build build-visionos-sim --config Release -- -quiet
@ -487,7 +479,7 @@ cmake -B build-tvos-sim -G Xcode \
-DCMAKE_XCODE_ATTRIBUTE_SUPPORTED_PLATFORMS=appletvsimulator \
-DCMAKE_C_FLAGS="${COMMON_C_FLAGS}" \
-DCMAKE_CXX_FLAGS="${COMMON_CXX_FLAGS}" \
-DLLAMA_OPENSSL=OFF \
-DLLAMA_CURL=OFF \
-S .
cmake --build build-tvos-sim --config Release -- -quiet
@ -502,7 +494,7 @@ cmake -B build-tvos-device -G Xcode \
-DCMAKE_XCODE_ATTRIBUTE_SUPPORTED_PLATFORMS=appletvos \
-DCMAKE_C_FLAGS="${COMMON_C_FLAGS}" \
-DCMAKE_CXX_FLAGS="${COMMON_CXX_FLAGS}" \
-DLLAMA_OPENSSL=OFF \
-DLLAMA_CURL=OFF \
-S .
cmake --build build-tvos-device --config Release -- -quiet

View File

@ -1,35 +0,0 @@
## Running MUSA CI in a Docker Container
Assuming `$PWD` is the root of the `llama.cpp` repository, follow these steps to set up and run MUSA CI in a Docker container:
### 1. Create a local directory to store cached models, configuration files and venv:
```bash
mkdir -p $HOME/llama.cpp/ci-cache
```
### 2. Create a local directory to store CI run results:
```bash
mkdir -p $HOME/llama.cpp/ci-results
```
### 3. Start a Docker container and run the CI:
```bash
docker run --privileged -it \
-v $HOME/llama.cpp/ci-cache:/ci-cache \
-v $HOME/llama.cpp/ci-results:/ci-results \
-v $PWD:/ws -w /ws \
mthreads/musa:rc4.3.0-devel-ubuntu22.04-amd64
```
Inside the container, execute the following commands:
```bash
apt update -y && apt install -y bc cmake ccache git python3.10-venv time unzip wget
git config --global --add safe.directory /ws
GG_BUILD_MUSA=1 bash ./ci/run.sh /ci-results /ci-cache
```
This setup ensures that the CI runs within an isolated Docker environment while maintaining cached files and results across runs.

View File

@ -1,10 +1,18 @@
# CI
This CI implements heavy-duty workflows that run on self-hosted runners. Typically the purpose of these workflows is to
cover hardware configurations that are not available from Github-hosted runners and/or require more computational
resource than normally available.
In addition to [Github Actions](https://github.com/ggml-org/llama.cpp/actions) `llama.cpp` uses a custom CI framework:
It is a good practice, before publishing changes to execute the full CI locally on your machine. For example:
https://github.com/ggml-org/ci
It monitors the `master` branch for new commits and runs the
[ci/run.sh](https://github.com/ggml-org/llama.cpp/blob/master/ci/run.sh) script on dedicated cloud instances. This allows us
to execute heavier workloads compared to just using Github Actions. Also with time, the cloud instances will be scaled
to cover various hardware architectures, including GPU and Apple Silicon instances.
Collaborators can optionally trigger the CI run by adding the `ggml-ci` keyword to their commit message.
Only the branches of this repo are monitored for this keyword.
It is a good practice, before publishing changes to execute the full CI locally on your machine:
```bash
mkdir tmp
@ -21,13 +29,40 @@ GG_BUILD_SYCL=1 bash ./ci/run.sh ./tmp/results ./tmp/mnt
# with MUSA support
GG_BUILD_MUSA=1 bash ./ci/run.sh ./tmp/results ./tmp/mnt
# etc.
```
# Adding self-hosted runners
## Running MUSA CI in a Docker Container
- Add a self-hosted `ggml-ci` workflow to [[.github/workflows/build.yml]] with an appropriate label
- Request a runner token from `ggml-org` (for example, via a comment in the PR or email)
- Set-up a machine using the received token ([docs](https://docs.github.com/en/actions/how-tos/manage-runners/self-hosted-runners/add-runners))
- Optionally update [ci/run.sh](https://github.com/ggml-org/llama.cpp/blob/master/ci/run.sh) to build and run on the target platform by gating the implementation with a `GG_BUILD_...` env
Assuming `$PWD` is the root of the `llama.cpp` repository, follow these steps to set up and run MUSA CI in a Docker container:
### 1. Create a local directory to store cached models, configuration files and venv:
```bash
mkdir -p $HOME/llama.cpp/ci-cache
```
### 2. Create a local directory to store CI run results:
```bash
mkdir -p $HOME/llama.cpp/ci-results
```
### 3. Start a Docker container and run the CI:
```bash
docker run --privileged -it \
-v $HOME/llama.cpp/ci-cache:/ci-cache \
-v $HOME/llama.cpp/ci-results:/ci-results \
-v $PWD:/ws -w /ws \
mthreads/musa:rc3.1.1-devel-ubuntu22.04
```
Inside the container, execute the following commands:
```bash
apt update -y && apt install -y bc cmake ccache git python3.10-venv time unzip wget
git config --global --add safe.directory /ws
GG_BUILD_MUSA=1 bash ./ci/run.sh /ci-results /ci-cache
```
This setup ensures that the CI runs within an isolated Docker environment while maintaining cached files and results across runs.

621
ci/run.sh
View File

@ -1,4 +1,4 @@
#!/usr/bin/env bash
#!/bin/bash
#
# sample usage:
#
@ -16,15 +16,9 @@
# # with VULKAN support
# GG_BUILD_VULKAN=1 bash ./ci/run.sh ./tmp/results ./tmp/mnt
#
# # with WebGPU support
# GG_BUILD_WEBGPU=1 bash ./ci/run.sh ./tmp/results ./tmp/mnt
#
# # with MUSA support
# GG_BUILD_MUSA=1 bash ./ci/run.sh ./tmp/results ./tmp/mnt
#
# # with KLEIDIAI support
# GG_BUILD_KLEIDIAI=1 bash ./ci/run.sh ./tmp/results ./tmp/mnt
#
if [ -z "$2" ]; then
echo "usage: $0 <output-dir> <mnt-dir>"
@ -37,46 +31,22 @@ mkdir -p "$2"
OUT=$(realpath "$1")
MNT=$(realpath "$2")
rm -f $OUT/*.log
rm -f $OUT/*.exit
rm -f $OUT/*.md
rm -f "$OUT/*.log"
rm -f "$OUT/*.exit"
rm -f "$OUT/*.md"
sd=`dirname $0`
cd $sd/../
SRC=`pwd`
CMAKE_EXTRA="-DLLAMA_FATAL_WARNINGS=${LLAMA_FATAL_WARNINGS:-ON} -DLLAMA_OPENSSL=OFF -DGGML_SCHED_NO_REALLOC=ON"
CMAKE_EXTRA="-DLLAMA_FATAL_WARNINGS=ON -DLLAMA_CURL=OFF"
if [ ! -z ${GG_BUILD_METAL} ]; then
CMAKE_EXTRA="${CMAKE_EXTRA} -DGGML_METAL=ON"
CMAKE_EXTRA="${CMAKE_EXTRA} -DGGML_METAL=ON -DGGML_METAL_USE_BF16=ON"
fi
if [ ! -z ${GG_BUILD_CUDA} ]; then
# TODO: Remove GGML_CUDA_CUB_3DOT2 flag once CCCL 3.2 is bundled within CTK and that CTK version is used in this project
CMAKE_EXTRA="${CMAKE_EXTRA} -DGGML_CUDA=ON -DGGML_CUDA_CUB_3DOT2=ON"
if command -v nvidia-smi >/dev/null 2>&1; then
CUDA_ARCH=$(nvidia-smi --query-gpu=compute_cap --format=csv,noheader,nounits 2>/dev/null | head -1 | tr -d '.')
if [[ -n "$CUDA_ARCH" && "$CUDA_ARCH" =~ ^[0-9]+$ ]]; then
CMAKE_EXTRA="${CMAKE_EXTRA} -DCMAKE_CUDA_ARCHITECTURES=${CUDA_ARCH}"
else
echo "Warning: Using fallback CUDA architectures"
CMAKE_EXTRA="${CMAKE_EXTRA} -DCMAKE_CUDA_ARCHITECTURES=61;70;75;80;86;89"
fi
else
echo "Error: nvidia-smi not found, cannot build with CUDA"
exit 1
fi
fi
if [ ! -z ${GG_BUILD_ROCM} ]; then
CMAKE_EXTRA="${CMAKE_EXTRA} -DGGML_HIP=ON"
if [ -z ${GG_BUILD_AMDGPU_TARGETS} ]; then
echo "Missing GG_BUILD_AMDGPU_TARGETS, please set it to your GPU architecture (e.g. gfx90a, gfx1100, etc.)"
exit 1
fi
CMAKE_EXTRA="${CMAKE_EXTRA} -DGPU_TARGETS=${GG_BUILD_AMDGPU_TARGETS}"
CMAKE_EXTRA="${CMAKE_EXTRA} -DGGML_CUDA=ON -DCMAKE_CUDA_ARCHITECTURES=native"
fi
if [ ! -z ${GG_BUILD_SYCL} ]; then
@ -96,29 +66,6 @@ fi
if [ ! -z ${GG_BUILD_VULKAN} ]; then
CMAKE_EXTRA="${CMAKE_EXTRA} -DGGML_VULKAN=1"
# if on Mac, disable METAL
if [[ "$OSTYPE" == "darwin"* ]]; then
CMAKE_EXTRA="${CMAKE_EXTRA} -DGGML_METAL=OFF -DGGML_BLAS=OFF"
fi
fi
if [ ! -z ${GG_BUILD_WEBGPU} ]; then
CMAKE_EXTRA="${CMAKE_EXTRA} -DGGML_WEBGPU=1 -DGGML_METAL=OFF -DGGML_BLAS=OFF"
if [ ! -z "${GG_BUILD_WEBGPU_DAWN_PREFIX}" ]; then
if [ -z "${CMAKE_PREFIX_PATH}" ]; then
export CMAKE_PREFIX_PATH="${GG_BUILD_WEBGPU_DAWN_PREFIX}"
else
export CMAKE_PREFIX_PATH="${GG_BUILD_WEBGPU_DAWN_PREFIX}:${CMAKE_PREFIX_PATH}"
fi
fi
# For some systems, Dawn_DIR needs to be set explicitly, e.g., the lib64 path
if [ ! -z "${GG_BUILD_WEBGPU_DAWN_DIR}" ]; then
CMAKE_EXTRA="${CMAKE_EXTRA} -DDawn_DIR=${GG_BUILD_WEBGPU_DAWN_DIR}"
fi
fi
if [ ! -z ${GG_BUILD_MUSA} ]; then
@ -126,45 +73,6 @@ if [ ! -z ${GG_BUILD_MUSA} ]; then
MUSA_ARCH=${MUSA_ARCH:-21}
CMAKE_EXTRA="${CMAKE_EXTRA} -DGGML_MUSA=ON -DMUSA_ARCHITECTURES=${MUSA_ARCH}"
fi
if [ ! -z ${GG_BUILD_NO_SVE} ]; then
# arm 9 and newer enables sve by default, adjust these flags depending on the cpu used
CMAKE_EXTRA="${CMAKE_EXTRA} -DGGML_NATIVE=OFF -DGGML_CPU_ARM_ARCH=armv8.5-a+fp16+i8mm"
fi
if [ -n "${GG_BUILD_KLEIDIAI}" ]; then
echo ">>===== Enabling KleidiAI support"
CANDIDATES=(
"armv9-a+dotprod+i8mm+sve2"
"armv9-a+dotprod+i8mm"
"armv8.6-a+dotprod+i8mm"
"armv8.2-a+dotprod"
)
CPU=""
for cpu in "${CANDIDATES[@]}"; do
if echo 'int main(){}' | ${CXX:-c++} -march="$cpu" -x c++ - -c -o /dev/null >/dev/null 2>&1; then
CPU="$cpu"
break
fi
done
if [ -z "$CPU" ]; then
echo "ERROR: None of the required ARM baselines (armv9/armv8.6/armv8.2 + dotprod) are supported by this compiler."
exit 1
fi
echo ">>===== Using ARM baseline: ${CPU}"
CMAKE_EXTRA="${CMAKE_EXTRA:+$CMAKE_EXTRA } \
-DGGML_NATIVE=OFF \
-DGGML_CPU_KLEIDIAI=ON \
-DGGML_CPU_AARCH64=ON \
-DGGML_CPU_ARM_ARCH=${CPU} \
-DBUILD_SHARED_LIBS=OFF"
fi
## helpers
# download a file if it does not exist or if it is outdated
@ -178,7 +86,7 @@ function gg_wget {
cd $out
# should not re-download if file is the same
wget -nv -c -N $url
wget -nv -N $url
cd $cwd
}
@ -222,7 +130,7 @@ function gg_run_ctest_debug {
(time cmake -DCMAKE_BUILD_TYPE=Debug ${CMAKE_EXTRA} .. ) 2>&1 | tee -a $OUT/${ci}-cmake.log
(time make -j$(nproc) ) 2>&1 | tee -a $OUT/${ci}-make.log
(time ctest --output-on-failure -L main -E "test-opt|test-backend-ops" ) 2>&1 | tee -a $OUT/${ci}-ctest.log
(time ctest --output-on-failure -L main -E test-opt ) 2>&1 | tee -a $OUT/${ci}-ctest.log
set +e
}
@ -254,7 +162,7 @@ function gg_run_ctest_release {
(time make -j$(nproc) ) 2>&1 | tee -a $OUT/${ci}-make.log
if [ -z ${GG_BUILD_LOW_PERF} ]; then
(time ctest --output-on-failure -L 'main|python' ) 2>&1 | tee -a $OUT/${ci}-ctest.log
(time ctest --output-on-failure -L main ) 2>&1 | tee -a $OUT/${ci}-ctest.log
else
(time ctest --output-on-failure -L main -E test-opt ) 2>&1 | tee -a $OUT/${ci}-ctest.log
fi
@ -272,23 +180,47 @@ function gg_sum_ctest_release {
gg_printf '```\n'
}
# test_scripts
# test_scripts_debug
function gg_run_test_scripts {
function gg_run_test_scripts_debug {
cd ${SRC}
set -e
(cd ./tools/gguf-split && time bash tests.sh "$SRC/build-ci-release/bin" "$MNT/models") 2>&1 | tee -a $OUT/${ci}-scripts.log
(cd ./tools/quantize && time bash tests.sh "$SRC/build-ci-release/bin" "$MNT/models") 2>&1 | tee -a $OUT/${ci}-scripts.log
(cd ./examples/gguf-split && time bash tests.sh "$SRC/build-ci-debug/bin" "$MNT/models") 2>&1 | tee -a $OUT/${ci}-scripts.log
(cd ./examples/quantize && time bash tests.sh "$SRC/build-ci-debug/bin" "$MNT/models") 2>&1 | tee -a $OUT/${ci}-scripts.log
set +e
}
function gg_sum_test_scripts {
function gg_sum_test_scripts_debug {
gg_printf '### %s\n\n' "${ci}"
gg_printf 'Runs test scripts\n'
gg_printf 'Runs test scripts in debug mode\n'
gg_printf '- status: %s\n' "$(cat $OUT/${ci}.exit)"
gg_printf '```\n'
gg_printf '%s\n' "$(cat $OUT/${ci}-scripts.log)"
gg_printf '```\n'
gg_printf '\n'
}
# test_scripts_release
function gg_run_test_scripts_release {
cd ${SRC}
set -e
(cd ./examples/gguf-split && time bash tests.sh "$SRC/build-ci-release/bin" "$MNT/models") 2>&1 | tee -a $OUT/${ci}-scripts.log
(cd ./examples/quantize && time bash tests.sh "$SRC/build-ci-release/bin" "$MNT/models") 2>&1 | tee -a $OUT/${ci}-scripts.log
set +e
}
function gg_sum_test_scripts_release {
gg_printf '### %s\n\n' "${ci}"
gg_printf 'Runs test scripts in release mode\n'
gg_printf '- status: %s\n' "$(cat $OUT/${ci}.exit)"
gg_printf '```\n'
gg_printf '%s\n' "$(cat $OUT/${ci}-scripts.log)"
@ -297,10 +229,15 @@ function gg_sum_test_scripts {
}
function gg_get_model {
#local gguf_0="$MNT/models/qwen3/0.6B/ggml-model-f16.gguf"
local gguf_0="$MNT/models/qwen3/0.6B/ggml-model-q4_0.gguf"
local gguf_0="$MNT/models/pythia/1.4B/ggml-model-f16.gguf"
local gguf_1="$MNT/models/pythia/2.8B/ggml-model-f16.gguf"
local gguf_2="$MNT/models/open-llama/7B-v2/ggml-model-f16.gguf"
if [[ -s $gguf_0 ]]; then
echo -n "$gguf_0"
elif [[ -s $gguf_1 ]]; then
echo -n "$gguf_1"
elif [[ -s $gguf_2 ]]; then
echo -n "$gguf_2"
else
echo >&2 "No model found. Can't run gg_run_ctest_with_model."
exit 1
@ -313,9 +250,7 @@ function gg_run_ctest_with_model_debug {
local model; model=$(gg_get_model)
cd build-ci-debug
set -e
(LLAMACPP_TEST_MODELFILE="$model" time ctest --output-on-failure -L model) 2>&1 | tee -a $OUT/${ci}-ctest.log
set +e
cd ..
}
@ -326,15 +261,7 @@ function gg_run_ctest_with_model_release {
local model; model=$(gg_get_model)
cd build-ci-release
set -e
(LLAMACPP_TEST_MODELFILE="$model" time ctest --output-on-failure -L model) 2>&1 | tee -a $OUT/${ci}-ctest.log
# test memory leaks
#if [[ ! -z ${GG_BUILD_METAL} ]]; then
# # TODO: this hangs for some reason ...
# (time leaks -quiet -atExit -- ./bin/test-thread-safety -m $model --parallel 2 -t 2 -p "hello") 2>&1 | tee -a $OUT/${ci}-leaks.log
#fi
set +e
cd ..
}
@ -359,22 +286,24 @@ function gg_sum_ctest_with_model_release {
gg_printf '```\n'
}
# qwen3_0_6b
# open_llama_7b_v2
function gg_run_qwen3_0_6b {
function gg_run_open_llama_7b_v2 {
cd ${SRC}
gg_wget models-mnt/qwen3/0.6B/ https://huggingface.co/Qwen/Qwen3-0.6B-Base/raw/main/config.json
gg_wget models-mnt/qwen3/0.6B/ https://huggingface.co/Qwen/Qwen3-0.6B-Base/raw/main/tokenizer.json
gg_wget models-mnt/qwen3/0.6B/ https://huggingface.co/Qwen/Qwen3-0.6B-Base/raw/main/tokenizer_config.json
#gg_wget models-mnt/qwen3/0.6B/ https://huggingface.co/Qwen/Qwen3-0.6B-Base/raw/main/special_tokens_map.json
gg_wget models-mnt/qwen3/0.6B/ https://huggingface.co/Qwen/Qwen3-0.6B-Base/resolve/main/model.safetensors
gg_wget models-mnt/open-llama/7B-v2/ https://huggingface.co/openlm-research/open_llama_7b_v2/raw/main/config.json
gg_wget models-mnt/open-llama/7B-v2/ https://huggingface.co/openlm-research/open_llama_7b_v2/resolve/main/tokenizer.model
gg_wget models-mnt/open-llama/7B-v2/ https://huggingface.co/openlm-research/open_llama_7b_v2/raw/main/tokenizer_config.json
gg_wget models-mnt/open-llama/7B-v2/ https://huggingface.co/openlm-research/open_llama_7b_v2/raw/main/special_tokens_map.json
gg_wget models-mnt/open-llama/7B-v2/ https://huggingface.co/openlm-research/open_llama_7b_v2/raw/main/pytorch_model.bin.index.json
gg_wget models-mnt/open-llama/7B-v2/ https://huggingface.co/openlm-research/open_llama_7b_v2/resolve/main/pytorch_model-00001-of-00002.bin
gg_wget models-mnt/open-llama/7B-v2/ https://huggingface.co/openlm-research/open_llama_7b_v2/resolve/main/pytorch_model-00002-of-00002.bin
gg_wget models-mnt/open-llama/7B-v2/ https://huggingface.co/openlm-research/open_llama_7b_v2/raw/main/generation_config.json
gg_wget models-mnt/wikitext/ https://huggingface.co/datasets/ggml-org/ci/resolve/main/wikitext-2-raw-v1.zip
unzip -o models-mnt/wikitext/wikitext-2-raw-v1.zip -d models-mnt/wikitext/
path_models="../models-mnt/qwen3/0.6B"
path_models="../models-mnt/open-llama/7B-v2"
path_wiki="../models-mnt/wikitext/wikitext-2-raw"
rm -rf build-ci-release && mkdir build-ci-release && cd build-ci-release
@ -384,11 +313,9 @@ function gg_run_qwen3_0_6b {
(time cmake -DCMAKE_BUILD_TYPE=Release ${CMAKE_EXTRA} .. ) 2>&1 | tee -a $OUT/${ci}-cmake.log
(time make -j$(nproc) ) 2>&1 | tee -a $OUT/${ci}-make.log
python3 ../convert_hf_to_gguf.py ${path_models} --outfile ${path_models}/ggml-model-f16.gguf --outtype f16
python3 ../convert_hf_to_gguf.py ${path_models} --outfile ${path_models}/ggml-model-bf16.gguf --outtype bf16
python3 ../examples/convert_legacy_llama.py ${path_models} --outfile ${path_models}/ggml-model-f16.gguf
model_f16="${path_models}/ggml-model-f16.gguf"
model_bf16="${path_models}/ggml-model-bf16.gguf"
model_q8_0="${path_models}/ggml-model-q8_0.gguf"
model_q4_0="${path_models}/ggml-model-q4_0.gguf"
model_q4_1="${path_models}/ggml-model-q4_1.gguf"
@ -402,53 +329,179 @@ function gg_run_qwen3_0_6b {
wiki_test="${path_wiki}/wiki.test.raw"
./bin/llama-quantize ${model_bf16} ${model_q8_0} q8_0 $(nproc)
./bin/llama-quantize ${model_bf16} ${model_q4_0} q4_0 $(nproc)
./bin/llama-quantize ${model_bf16} ${model_q4_1} q4_1 $(nproc)
./bin/llama-quantize ${model_bf16} ${model_q5_0} q5_0 $(nproc)
./bin/llama-quantize ${model_bf16} ${model_q5_1} q5_1 $(nproc)
./bin/llama-quantize ${model_bf16} ${model_q2_k} q2_k $(nproc)
./bin/llama-quantize ${model_bf16} ${model_q3_k} q3_k $(nproc)
./bin/llama-quantize ${model_bf16} ${model_q4_k} q4_k $(nproc)
./bin/llama-quantize ${model_bf16} ${model_q5_k} q5_k $(nproc)
./bin/llama-quantize ${model_bf16} ${model_q6_k} q6_k $(nproc)
./bin/llama-quantize ${model_f16} ${model_q8_0} q8_0
./bin/llama-quantize ${model_f16} ${model_q4_0} q4_0
./bin/llama-quantize ${model_f16} ${model_q4_1} q4_1
./bin/llama-quantize ${model_f16} ${model_q5_0} q5_0
./bin/llama-quantize ${model_f16} ${model_q5_1} q5_1
./bin/llama-quantize ${model_f16} ${model_q2_k} q2_k
./bin/llama-quantize ${model_f16} ${model_q3_k} q3_k
./bin/llama-quantize ${model_f16} ${model_q4_k} q4_k
./bin/llama-quantize ${model_f16} ${model_q5_k} q5_k
./bin/llama-quantize ${model_f16} ${model_q6_k} q6_k
(time ./bin/llama-fit-params --model ${model_f16} 2>&1 | tee -a $OUT/${ci}-fp-f16.log)
(time ./bin/llama-cli -no-cnv --model ${model_f16} -t 1 -ngl 99 -c 0 -s 1234 -n 256 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-f16.log
(time ./bin/llama-cli -no-cnv --model ${model_q8_0} -t 1 -ngl 99 -c 0 -s 1234 -n 256 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q8_0.log
(time ./bin/llama-cli -no-cnv --model ${model_q4_0} -t 1 -ngl 99 -c 0 -s 1234 -n 256 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q4_0.log
(time ./bin/llama-cli -no-cnv --model ${model_q4_1} -t 1 -ngl 99 -c 0 -s 1234 -n 256 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q4_1.log
(time ./bin/llama-cli -no-cnv --model ${model_q5_0} -t 1 -ngl 99 -c 0 -s 1234 -n 256 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q5_0.log
(time ./bin/llama-cli -no-cnv --model ${model_q5_1} -t 1 -ngl 99 -c 0 -s 1234 -n 256 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q5_1.log
(time ./bin/llama-cli -no-cnv --model ${model_q2_k} -t 1 -ngl 99 -c 0 -s 1234 -n 256 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q2_k.log
(time ./bin/llama-cli -no-cnv --model ${model_q3_k} -t 1 -ngl 99 -c 0 -s 1234 -n 256 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q3_k.log
(time ./bin/llama-cli -no-cnv --model ${model_q4_k} -t 1 -ngl 99 -c 0 -s 1234 -n 256 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q4_k.log
(time ./bin/llama-cli -no-cnv --model ${model_q5_k} -t 1 -ngl 99 -c 0 -s 1234 -n 256 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q5_k.log
(time ./bin/llama-cli -no-cnv --model ${model_q6_k} -t 1 -ngl 99 -c 0 -s 1234 -n 256 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q6_k.log
(time ./bin/llama-completion -no-cnv --model ${model_f16} -ngl 99 -c 1024 -s 1234 -n 64 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-f16.log
(time ./bin/llama-completion -no-cnv --model ${model_bf16} -ngl 99 -c 1024 -s 1234 -n 64 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-bf16.log
(time ./bin/llama-completion -no-cnv --model ${model_q8_0} -ngl 99 -c 1024 -s 1234 -n 64 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q8_0.log
(time ./bin/llama-completion -no-cnv --model ${model_q4_0} -ngl 99 -c 1024 -s 1234 -n 64 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q4_0.log
(time ./bin/llama-completion -no-cnv --model ${model_q4_1} -ngl 99 -c 1024 -s 1234 -n 64 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q4_1.log
(time ./bin/llama-completion -no-cnv --model ${model_q5_0} -ngl 99 -c 1024 -s 1234 -n 64 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q5_0.log
(time ./bin/llama-completion -no-cnv --model ${model_q5_1} -ngl 99 -c 1024 -s 1234 -n 64 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q5_1.log
(time ./bin/llama-completion -no-cnv --model ${model_q2_k} -ngl 99 -c 1024 -s 1234 -n 64 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q2_k.log
(time ./bin/llama-completion -no-cnv --model ${model_q3_k} -ngl 99 -c 1024 -s 1234 -n 64 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q3_k.log
(time ./bin/llama-completion -no-cnv --model ${model_q4_k} -ngl 99 -c 1024 -s 1234 -n 64 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q4_k.log
(time ./bin/llama-completion -no-cnv --model ${model_q5_k} -ngl 99 -c 1024 -s 1234 -n 64 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q5_k.log
(time ./bin/llama-completion -no-cnv --model ${model_q6_k} -ngl 99 -c 1024 -s 1234 -n 64 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q6_k.log
(time ./bin/llama-perplexity --model ${model_f16} -f ${wiki_test} -t 1 -ngl 99 -c 2048 -b 512 --chunks 4 ) 2>&1 | tee -a $OUT/${ci}-tg-f16.log
(time ./bin/llama-perplexity --model ${model_q8_0} -f ${wiki_test} -t 1 -ngl 99 -c 2048 -b 512 --chunks 4 ) 2>&1 | tee -a $OUT/${ci}-tg-q8_0.log
(time ./bin/llama-perplexity --model ${model_q4_0} -f ${wiki_test} -t 1 -ngl 99 -c 2048 -b 512 --chunks 4 ) 2>&1 | tee -a $OUT/${ci}-tg-q4_0.log
(time ./bin/llama-perplexity --model ${model_q4_1} -f ${wiki_test} -t 1 -ngl 99 -c 2048 -b 512 --chunks 4 ) 2>&1 | tee -a $OUT/${ci}-tg-q4_1.log
(time ./bin/llama-perplexity --model ${model_q5_0} -f ${wiki_test} -t 1 -ngl 99 -c 2048 -b 512 --chunks 4 ) 2>&1 | tee -a $OUT/${ci}-tg-q5_0.log
(time ./bin/llama-perplexity --model ${model_q5_1} -f ${wiki_test} -t 1 -ngl 99 -c 2048 -b 512 --chunks 4 ) 2>&1 | tee -a $OUT/${ci}-tg-q5_1.log
(time ./bin/llama-perplexity --model ${model_q2_k} -f ${wiki_test} -t 1 -ngl 99 -c 2048 -b 512 --chunks 4 ) 2>&1 | tee -a $OUT/${ci}-tg-q2_k.log
(time ./bin/llama-perplexity --model ${model_q3_k} -f ${wiki_test} -t 1 -ngl 99 -c 2048 -b 512 --chunks 4 ) 2>&1 | tee -a $OUT/${ci}-tg-q3_k.log
(time ./bin/llama-perplexity --model ${model_q4_k} -f ${wiki_test} -t 1 -ngl 99 -c 2048 -b 512 --chunks 4 ) 2>&1 | tee -a $OUT/${ci}-tg-q4_k.log
(time ./bin/llama-perplexity --model ${model_q5_k} -f ${wiki_test} -t 1 -ngl 99 -c 2048 -b 512 --chunks 4 ) 2>&1 | tee -a $OUT/${ci}-tg-q5_k.log
(time ./bin/llama-perplexity --model ${model_q6_k} -f ${wiki_test} -t 1 -ngl 99 -c 2048 -b 512 --chunks 4 ) 2>&1 | tee -a $OUT/${ci}-tg-q6_k.log
(time ./bin/llama-perplexity --model ${model_f16} -f ${wiki_test} -ngl 99 -c 1024 -b 512 --chunks 2 ) 2>&1 | tee -a $OUT/${ci}-tg-f16.log
if [ -z ${GG_BUILD_NO_BF16} ]; then
(time ./bin/llama-perplexity --model ${model_bf16} -f ${wiki_test} -ngl 99 -c 1024 -b 512 --chunks 2 ) 2>&1 | tee -a $OUT/${ci}-tg-bf16.log
fi
(time ./bin/llama-perplexity --model ${model_q8_0} -f ${wiki_test} -ngl 99 -c 1024 -b 512 --chunks 2 ) 2>&1 | tee -a $OUT/${ci}-tg-q8_0.log
(time ./bin/llama-perplexity --model ${model_q4_0} -f ${wiki_test} -ngl 99 -c 1024 -b 512 --chunks 2 ) 2>&1 | tee -a $OUT/${ci}-tg-q4_0.log
(time ./bin/llama-perplexity --model ${model_q4_1} -f ${wiki_test} -ngl 99 -c 1024 -b 512 --chunks 2 ) 2>&1 | tee -a $OUT/${ci}-tg-q4_1.log
(time ./bin/llama-perplexity --model ${model_q5_0} -f ${wiki_test} -ngl 99 -c 1024 -b 512 --chunks 2 ) 2>&1 | tee -a $OUT/${ci}-tg-q5_0.log
(time ./bin/llama-perplexity --model ${model_q5_1} -f ${wiki_test} -ngl 99 -c 1024 -b 512 --chunks 2 ) 2>&1 | tee -a $OUT/${ci}-tg-q5_1.log
(time ./bin/llama-perplexity --model ${model_q2_k} -f ${wiki_test} -ngl 99 -c 1024 -b 512 --chunks 2 ) 2>&1 | tee -a $OUT/${ci}-tg-q2_k.log
(time ./bin/llama-perplexity --model ${model_q3_k} -f ${wiki_test} -ngl 99 -c 1024 -b 512 --chunks 2 ) 2>&1 | tee -a $OUT/${ci}-tg-q3_k.log
(time ./bin/llama-perplexity --model ${model_q4_k} -f ${wiki_test} -ngl 99 -c 1024 -b 512 --chunks 2 ) 2>&1 | tee -a $OUT/${ci}-tg-q4_k.log
(time ./bin/llama-perplexity --model ${model_q5_k} -f ${wiki_test} -ngl 99 -c 1024 -b 512 --chunks 2 ) 2>&1 | tee -a $OUT/${ci}-tg-q5_k.log
(time ./bin/llama-perplexity --model ${model_q6_k} -f ${wiki_test} -ngl 99 -c 1024 -b 512 --chunks 2 ) 2>&1 | tee -a $OUT/${ci}-tg-q6_k.log
(time ./bin/llama-imatrix --model ${model_f16} -f ${wiki_test} -t 1 -ngl 99 -c 2048 -b 512 --chunks 4 ) 2>&1 | tee -a $OUT/${ci}-imatrix.log
(time ./bin/llama-imatrix --model ${model_f16} -f ${wiki_test} -ngl 99 -c 1024 -b 512 --chunks 2 ) 2>&1 | tee -a $OUT/${ci}-imatrix.log
(time ./bin/llama-save-load-state --model ${model_q4_0} -ngl 10 -c 1024 -fa off --no-op-offload) 2>&1 | tee -a $OUT/${ci}-save-load-state.log
(time ./bin/llama-save-load-state --model ${model_q4_0} -ngl 10 -c 1024 -fa on --no-op-offload) 2>&1 | tee -a $OUT/${ci}-save-load-state.log
(time ./bin/llama-save-load-state --model ${model_q4_0} -ngl 99 -c 1024 -fa off ) 2>&1 | tee -a $OUT/${ci}-save-load-state.log
(time ./bin/llama-save-load-state --model ${model_q4_0} -ngl 99 -c 1024 -fa on ) 2>&1 | tee -a $OUT/${ci}-save-load-state.log
(time ./bin/llama-save-load-state --model ${model_q4_0} -ngl 10 -c 0 ) 2>&1 | tee -a $OUT/${ci}-save-load-state.log
(time ./bin/llama-save-load-state --model ${model_q4_0} -ngl 10 -c 0 -fa ) 2>&1 | tee -a $OUT/${ci}-save-load-state.log
(time ./bin/llama-save-load-state --model ${model_q4_0} -ngl 99 -c 0 ) 2>&1 | tee -a $OUT/${ci}-save-load-state.log
(time ./bin/llama-save-load-state --model ${model_q4_0} -ngl 99 -c 0 -fa ) 2>&1 | tee -a $OUT/${ci}-save-load-state.log
function check_ppl {
qnt="$1"
ppl=$(echo "$2" | grep -oE "[0-9]+\.[0-9]+" | tail -n 1)
if [ $(echo "$ppl > 20.0" | bc) -eq 1 ]; then
printf ' - %s @ %s (FAIL: ppl > 20.0)\n' "$qnt" "$ppl"
return 20
fi
printf ' - %s @ %s OK\n' "$qnt" "$ppl"
return 0
}
check_ppl "f16" "$(cat $OUT/${ci}-tg-f16.log | grep "^\[1\]")" | tee -a $OUT/${ci}-ppl.log
check_ppl "q8_0" "$(cat $OUT/${ci}-tg-q8_0.log | grep "^\[1\]")" | tee -a $OUT/${ci}-ppl.log
check_ppl "q4_0" "$(cat $OUT/${ci}-tg-q4_0.log | grep "^\[1\]")" | tee -a $OUT/${ci}-ppl.log
check_ppl "q4_1" "$(cat $OUT/${ci}-tg-q4_1.log | grep "^\[1\]")" | tee -a $OUT/${ci}-ppl.log
check_ppl "q5_0" "$(cat $OUT/${ci}-tg-q5_0.log | grep "^\[1\]")" | tee -a $OUT/${ci}-ppl.log
check_ppl "q5_1" "$(cat $OUT/${ci}-tg-q5_1.log | grep "^\[1\]")" | tee -a $OUT/${ci}-ppl.log
check_ppl "q2_k" "$(cat $OUT/${ci}-tg-q2_k.log | grep "^\[1\]")" | tee -a $OUT/${ci}-ppl.log
check_ppl "q3_k" "$(cat $OUT/${ci}-tg-q3_k.log | grep "^\[1\]")" | tee -a $OUT/${ci}-ppl.log
check_ppl "q4_k" "$(cat $OUT/${ci}-tg-q4_k.log | grep "^\[1\]")" | tee -a $OUT/${ci}-ppl.log
check_ppl "q5_k" "$(cat $OUT/${ci}-tg-q5_k.log | grep "^\[1\]")" | tee -a $OUT/${ci}-ppl.log
check_ppl "q6_k" "$(cat $OUT/${ci}-tg-q6_k.log | grep "^\[1\]")" | tee -a $OUT/${ci}-ppl.log
cat $OUT/${ci}-imatrix.log | grep "Final" >> $OUT/${ci}-imatrix-sum.log
set +e
}
function gg_sum_open_llama_7b_v2 {
gg_printf '### %s\n\n' "${ci}"
gg_printf 'OpenLLaMA 7B-v2:\n'
gg_printf '- status: %s\n' "$(cat $OUT/${ci}.exit)"
gg_printf '- perplexity:\n%s\n' "$(cat $OUT/${ci}-ppl.log)"
gg_printf '- imatrix:\n```\n%s\n```\n' "$(cat $OUT/${ci}-imatrix-sum.log)"
gg_printf '- f16: \n```\n%s\n```\n' "$(cat $OUT/${ci}-tg-f16.log)"
gg_printf '- q8_0:\n```\n%s\n```\n' "$(cat $OUT/${ci}-tg-q8_0.log)"
gg_printf '- q4_0:\n```\n%s\n```\n' "$(cat $OUT/${ci}-tg-q4_0.log)"
gg_printf '- q4_1:\n```\n%s\n```\n' "$(cat $OUT/${ci}-tg-q4_1.log)"
gg_printf '- q5_0:\n```\n%s\n```\n' "$(cat $OUT/${ci}-tg-q5_0.log)"
gg_printf '- q5_1:\n```\n%s\n```\n' "$(cat $OUT/${ci}-tg-q5_1.log)"
gg_printf '- q2_k:\n```\n%s\n```\n' "$(cat $OUT/${ci}-tg-q2_k.log)"
gg_printf '- q3_k:\n```\n%s\n```\n' "$(cat $OUT/${ci}-tg-q3_k.log)"
gg_printf '- q4_k:\n```\n%s\n```\n' "$(cat $OUT/${ci}-tg-q4_k.log)"
gg_printf '- q5_k:\n```\n%s\n```\n' "$(cat $OUT/${ci}-tg-q5_k.log)"
gg_printf '- q6_k:\n```\n%s\n```\n' "$(cat $OUT/${ci}-tg-q6_k.log)"
gg_printf '- save-load-state: \n```\n%s\n```\n' "$(cat $OUT/${ci}-save-load-state.log)"
}
# pythia_1.4b
function gg_run_pythia_1_4b {
cd ${SRC}
gg_wget models-mnt/pythia/1.4B/ https://huggingface.co/EleutherAI/pythia-1.4b/raw/main/config.json
gg_wget models-mnt/pythia/1.4B/ https://huggingface.co/EleutherAI/pythia-1.4b/raw/main/tokenizer.json
gg_wget models-mnt/pythia/1.4B/ https://huggingface.co/EleutherAI/pythia-1.4b/raw/main/tokenizer_config.json
gg_wget models-mnt/pythia/1.4B/ https://huggingface.co/EleutherAI/pythia-1.4b/raw/main/special_tokens_map.json
gg_wget models-mnt/pythia/1.4B/ https://huggingface.co/EleutherAI/pythia-1.4b/resolve/main/pytorch_model.bin
gg_wget models-mnt/wikitext/ https://huggingface.co/datasets/ggml-org/ci/resolve/main/wikitext-2-raw-v1.zip
unzip -o models-mnt/wikitext/wikitext-2-raw-v1.zip -d models-mnt/wikitext/
head -n 60 models-mnt/wikitext/wikitext-2-raw/wiki.test.raw > models-mnt/wikitext/wikitext-2-raw/wiki.test-60.raw
path_models="../models-mnt/pythia/1.4B"
path_wiki="../models-mnt/wikitext/wikitext-2-raw"
rm -rf build-ci-release && mkdir build-ci-release && cd build-ci-release
set -e
(time cmake -DCMAKE_BUILD_TYPE=Release ${CMAKE_EXTRA} .. ) 2>&1 | tee -a $OUT/${ci}-cmake.log
(time make -j$(nproc) ) 2>&1 | tee -a $OUT/${ci}-make.log
python3 ../convert_hf_to_gguf.py ${path_models} --outfile ${path_models}/ggml-model-f16.gguf
model_f16="${path_models}/ggml-model-f16.gguf"
model_q8_0="${path_models}/ggml-model-q8_0.gguf"
model_q4_0="${path_models}/ggml-model-q4_0.gguf"
model_q4_1="${path_models}/ggml-model-q4_1.gguf"
model_q5_0="${path_models}/ggml-model-q5_0.gguf"
model_q5_1="${path_models}/ggml-model-q5_1.gguf"
model_q2_k="${path_models}/ggml-model-q2_k.gguf"
model_q3_k="${path_models}/ggml-model-q3_k.gguf"
model_q4_k="${path_models}/ggml-model-q4_k.gguf"
model_q5_k="${path_models}/ggml-model-q5_k.gguf"
model_q6_k="${path_models}/ggml-model-q6_k.gguf"
wiki_test_60="${path_wiki}/wiki.test-60.raw"
./bin/llama-quantize ${model_f16} ${model_q8_0} q8_0
./bin/llama-quantize ${model_f16} ${model_q4_0} q4_0
./bin/llama-quantize ${model_f16} ${model_q4_1} q4_1
./bin/llama-quantize ${model_f16} ${model_q5_0} q5_0
./bin/llama-quantize ${model_f16} ${model_q5_1} q5_1
./bin/llama-quantize ${model_f16} ${model_q2_k} q2_k
./bin/llama-quantize ${model_f16} ${model_q3_k} q3_k
./bin/llama-quantize ${model_f16} ${model_q4_k} q4_k
./bin/llama-quantize ${model_f16} ${model_q5_k} q5_k
./bin/llama-quantize ${model_f16} ${model_q6_k} q6_k
(time ./bin/llama-cli -no-cnv --model ${model_f16} -ngl 99 -c 0 -s 1234 -n 64 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-f16.log
(time ./bin/llama-cli -no-cnv --model ${model_q8_0} -ngl 99 -c 0 -s 1234 -n 64 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q8_0.log
(time ./bin/llama-cli -no-cnv --model ${model_q4_0} -ngl 99 -c 0 -s 1234 -n 64 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q4_0.log
(time ./bin/llama-cli -no-cnv --model ${model_q4_1} -ngl 99 -c 0 -s 1234 -n 64 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q4_1.log
(time ./bin/llama-cli -no-cnv --model ${model_q5_0} -ngl 99 -c 0 -s 1234 -n 64 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q5_0.log
(time ./bin/llama-cli -no-cnv --model ${model_q5_1} -ngl 99 -c 0 -s 1234 -n 64 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q5_1.log
(time ./bin/llama-cli -no-cnv --model ${model_q2_k} -ngl 99 -c 0 -s 1234 -n 64 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q2_k.log
(time ./bin/llama-cli -no-cnv --model ${model_q3_k} -ngl 99 -c 0 -s 1234 -n 64 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q3_k.log
(time ./bin/llama-cli -no-cnv --model ${model_q4_k} -ngl 99 -c 0 -s 1234 -n 64 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q4_k.log
(time ./bin/llama-cli -no-cnv --model ${model_q5_k} -ngl 99 -c 0 -s 1234 -n 64 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q5_k.log
(time ./bin/llama-cli -no-cnv --model ${model_q6_k} -ngl 99 -c 0 -s 1234 -n 64 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q6_k.log
(time ./bin/llama-perplexity --model ${model_f16} -f ${wiki_test_60} -ngl 99 -c 128 -b 128 --chunks 1 ) 2>&1 | tee -a $OUT/${ci}-tg-f16.log
(time ./bin/llama-perplexity --model ${model_q8_0} -f ${wiki_test_60} -ngl 99 -c 128 -b 128 --chunks 1 ) 2>&1 | tee -a $OUT/${ci}-tg-q8_0.log
(time ./bin/llama-perplexity --model ${model_q4_0} -f ${wiki_test_60} -ngl 99 -c 128 -b 128 --chunks 1 ) 2>&1 | tee -a $OUT/${ci}-tg-q4_0.log
(time ./bin/llama-perplexity --model ${model_q4_1} -f ${wiki_test_60} -ngl 99 -c 128 -b 128 --chunks 1 ) 2>&1 | tee -a $OUT/${ci}-tg-q4_1.log
(time ./bin/llama-perplexity --model ${model_q5_0} -f ${wiki_test_60} -ngl 99 -c 128 -b 128 --chunks 1 ) 2>&1 | tee -a $OUT/${ci}-tg-q5_0.log
(time ./bin/llama-perplexity --model ${model_q5_1} -f ${wiki_test_60} -ngl 99 -c 128 -b 128 --chunks 1 ) 2>&1 | tee -a $OUT/${ci}-tg-q5_1.log
(time ./bin/llama-perplexity --model ${model_q2_k} -f ${wiki_test_60} -ngl 99 -c 128 -b 128 --chunks 1 ) 2>&1 | tee -a $OUT/${ci}-tg-q2_k.log
(time ./bin/llama-perplexity --model ${model_q3_k} -f ${wiki_test_60} -ngl 99 -c 128 -b 128 --chunks 1 ) 2>&1 | tee -a $OUT/${ci}-tg-q3_k.log
(time ./bin/llama-perplexity --model ${model_q4_k} -f ${wiki_test_60} -ngl 99 -c 128 -b 128 --chunks 1 ) 2>&1 | tee -a $OUT/${ci}-tg-q4_k.log
(time ./bin/llama-perplexity --model ${model_q5_k} -f ${wiki_test_60} -ngl 99 -c 128 -b 128 --chunks 1 ) 2>&1 | tee -a $OUT/${ci}-tg-q5_k.log
(time ./bin/llama-perplexity --model ${model_q6_k} -f ${wiki_test_60} -ngl 99 -c 128 -b 128 --chunks 1 ) 2>&1 | tee -a $OUT/${ci}-tg-q6_k.log
(time ./bin/llama-imatrix --model ${model_f16} -f ${wiki_test_60} -ngl 99 -c 128 -b 128 --chunks 1 ) 2>&1 | tee -a $OUT/${ci}-imatrix.log
(time ./bin/llama-save-load-state --model ${model_q4_0} -ngl 99 -c 0 ) 2>&1 | tee -a $OUT/${ci}-save-load-state.log
(time ./bin/llama-save-load-state --model ${model_q4_0} -ngl 99 -c 0 -fa ) 2>&1 | tee -a $OUT/${ci}-save-load-state.log
function check_ppl {
qnt="$1"
@ -464,9 +517,6 @@ function gg_run_qwen3_0_6b {
}
check_ppl "f16" "$(cat $OUT/${ci}-tg-f16.log | grep "^\[1\]")" | tee -a $OUT/${ci}-ppl.log
if [ -z ${GG_BUILD_NO_BF16} ]; then
check_ppl "bf16" "$(cat $OUT/${ci}-tg-bf16.log | grep "^\[1\]")" | tee -a $OUT/${ci}-ppl.log
fi
check_ppl "q8_0" "$(cat $OUT/${ci}-tg-q8_0.log | grep "^\[1\]")" | tee -a $OUT/${ci}-ppl.log
check_ppl "q4_0" "$(cat $OUT/${ci}-tg-q4_0.log | grep "^\[1\]")" | tee -a $OUT/${ci}-ppl.log
check_ppl "q4_1" "$(cat $OUT/${ci}-tg-q4_1.log | grep "^\[1\]")" | tee -a $OUT/${ci}-ppl.log
@ -483,17 +533,147 @@ function gg_run_qwen3_0_6b {
set +e
}
function gg_sum_qwen3_0_6b {
function gg_sum_pythia_1_4b {
gg_printf '### %s\n\n' "${ci}"
gg_printf 'Qwen3 0.6B:\n'
gg_printf 'Pythia 1.4B:\n'
gg_printf '- status: %s\n' "$(cat $OUT/${ci}.exit)"
gg_printf '- perplexity:\n%s\n' "$(cat $OUT/${ci}-ppl.log)"
gg_printf '- imatrix:\n```\n%s\n```\n' "$(cat $OUT/${ci}-imatrix-sum.log)"
gg_printf '- f16:\n```\n%s\n```\n' "$(cat $OUT/${ci}-tg-f16.log)"
if [ -z ${GG_BUILD_NO_BF16} ]; then
gg_printf '- bf16:\n```\n%s\n```\n' "$(cat $OUT/${ci}-tg-bf16.log)"
fi
gg_printf '- f16: \n```\n%s\n```\n' "$(cat $OUT/${ci}-tg-f16.log)"
gg_printf '- q8_0:\n```\n%s\n```\n' "$(cat $OUT/${ci}-tg-q8_0.log)"
gg_printf '- q4_0:\n```\n%s\n```\n' "$(cat $OUT/${ci}-tg-q4_0.log)"
gg_printf '- q4_1:\n```\n%s\n```\n' "$(cat $OUT/${ci}-tg-q4_1.log)"
gg_printf '- q5_0:\n```\n%s\n```\n' "$(cat $OUT/${ci}-tg-q5_0.log)"
gg_printf '- q5_1:\n```\n%s\n```\n' "$(cat $OUT/${ci}-tg-q5_1.log)"
gg_printf '- q2_k:\n```\n%s\n```\n' "$(cat $OUT/${ci}-tg-q2_k.log)"
gg_printf '- q3_k:\n```\n%s\n```\n' "$(cat $OUT/${ci}-tg-q3_k.log)"
gg_printf '- q4_k:\n```\n%s\n```\n' "$(cat $OUT/${ci}-tg-q4_k.log)"
gg_printf '- q5_k:\n```\n%s\n```\n' "$(cat $OUT/${ci}-tg-q5_k.log)"
gg_printf '- q6_k:\n```\n%s\n```\n' "$(cat $OUT/${ci}-tg-q6_k.log)"
gg_printf '- save-load-state: \n```\n%s\n```\n' "$(cat $OUT/${ci}-save-load-state.log)"
}
# pythia_2_8b
function gg_run_pythia_2_8b {
cd ${SRC}
gg_wget models-mnt/pythia/2.8B/ https://huggingface.co/EleutherAI/pythia-2.8b/raw/main/config.json
gg_wget models-mnt/pythia/2.8B/ https://huggingface.co/EleutherAI/pythia-2.8b/raw/main/tokenizer.json
gg_wget models-mnt/pythia/2.8B/ https://huggingface.co/EleutherAI/pythia-2.8b/raw/main/tokenizer_config.json
gg_wget models-mnt/pythia/2.8B/ https://huggingface.co/EleutherAI/pythia-2.8b/raw/main/special_tokens_map.json
gg_wget models-mnt/pythia/2.8B/ https://huggingface.co/EleutherAI/pythia-2.8b/resolve/main/pytorch_model.bin
gg_wget models-mnt/wikitext/ https://huggingface.co/datasets/ggml-org/ci/resolve/main/wikitext-2-raw-v1.zip
unzip -o models-mnt/wikitext/wikitext-2-raw-v1.zip -d models-mnt/wikitext/
path_models="../models-mnt/pythia/2.8B"
path_wiki="../models-mnt/wikitext/wikitext-2-raw"
rm -rf build-ci-release && mkdir build-ci-release && cd build-ci-release
set -e
(time cmake -DCMAKE_BUILD_TYPE=Release ${CMAKE_EXTRA} .. ) 2>&1 | tee -a $OUT/${ci}-cmake.log
(time make -j$(nproc) ) 2>&1 | tee -a $OUT/${ci}-make.log
python3 ../convert_hf_to_gguf.py ${path_models} --outfile ${path_models}/ggml-model-f16.gguf
model_f16="${path_models}/ggml-model-f16.gguf"
model_q8_0="${path_models}/ggml-model-q8_0.gguf"
model_q4_0="${path_models}/ggml-model-q4_0.gguf"
model_q4_1="${path_models}/ggml-model-q4_1.gguf"
model_q5_0="${path_models}/ggml-model-q5_0.gguf"
model_q5_1="${path_models}/ggml-model-q5_1.gguf"
model_q2_k="${path_models}/ggml-model-q2_k.gguf"
model_q3_k="${path_models}/ggml-model-q3_k.gguf"
model_q4_k="${path_models}/ggml-model-q4_k.gguf"
model_q5_k="${path_models}/ggml-model-q5_k.gguf"
model_q6_k="${path_models}/ggml-model-q6_k.gguf"
wiki_test="${path_wiki}/wiki.test.raw"
./bin/llama-quantize ${model_f16} ${model_q8_0} q8_0
./bin/llama-quantize ${model_f16} ${model_q4_0} q4_0
./bin/llama-quantize ${model_f16} ${model_q4_1} q4_1
./bin/llama-quantize ${model_f16} ${model_q5_0} q5_0
./bin/llama-quantize ${model_f16} ${model_q5_1} q5_1
./bin/llama-quantize ${model_f16} ${model_q2_k} q2_k
./bin/llama-quantize ${model_f16} ${model_q3_k} q3_k
./bin/llama-quantize ${model_f16} ${model_q4_k} q4_k
./bin/llama-quantize ${model_f16} ${model_q5_k} q5_k
./bin/llama-quantize ${model_f16} ${model_q6_k} q6_k
(time ./bin/llama-cli -no-cnv --model ${model_f16} -t 1 -ngl 99 -c 0 -s 1234 -n 256 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-f16.log
(time ./bin/llama-cli -no-cnv --model ${model_q8_0} -t 1 -ngl 99 -c 0 -s 1234 -n 256 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q8_0.log
(time ./bin/llama-cli -no-cnv --model ${model_q4_0} -t 1 -ngl 99 -c 0 -s 1234 -n 256 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q4_0.log
(time ./bin/llama-cli -no-cnv --model ${model_q4_1} -t 1 -ngl 99 -c 0 -s 1234 -n 256 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q4_1.log
(time ./bin/llama-cli -no-cnv --model ${model_q5_0} -t 1 -ngl 99 -c 0 -s 1234 -n 256 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q5_0.log
(time ./bin/llama-cli -no-cnv --model ${model_q5_1} -t 1 -ngl 99 -c 0 -s 1234 -n 256 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q5_1.log
(time ./bin/llama-cli -no-cnv --model ${model_q2_k} -t 1 -ngl 99 -c 0 -s 1234 -n 256 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q2_k.log
(time ./bin/llama-cli -no-cnv --model ${model_q3_k} -t 1 -ngl 99 -c 0 -s 1234 -n 256 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q3_k.log
(time ./bin/llama-cli -no-cnv --model ${model_q4_k} -t 1 -ngl 99 -c 0 -s 1234 -n 256 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q4_k.log
(time ./bin/llama-cli -no-cnv --model ${model_q5_k} -t 1 -ngl 99 -c 0 -s 1234 -n 256 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q5_k.log
(time ./bin/llama-cli -no-cnv --model ${model_q6_k} -t 1 -ngl 99 -c 0 -s 1234 -n 256 --ignore-eos -p "I believe the meaning of life is" ) 2>&1 | tee -a $OUT/${ci}-tg-q6_k.log
(time ./bin/llama-perplexity --model ${model_f16} -f ${wiki_test} -t 1 -ngl 99 -c 2048 -b 512 --chunks 4 ) 2>&1 | tee -a $OUT/${ci}-tg-f16.log
(time ./bin/llama-perplexity --model ${model_q8_0} -f ${wiki_test} -t 1 -ngl 99 -c 2048 -b 512 --chunks 4 ) 2>&1 | tee -a $OUT/${ci}-tg-q8_0.log
(time ./bin/llama-perplexity --model ${model_q4_0} -f ${wiki_test} -t 1 -ngl 99 -c 2048 -b 512 --chunks 4 ) 2>&1 | tee -a $OUT/${ci}-tg-q4_0.log
(time ./bin/llama-perplexity --model ${model_q4_1} -f ${wiki_test} -t 1 -ngl 99 -c 2048 -b 512 --chunks 4 ) 2>&1 | tee -a $OUT/${ci}-tg-q4_1.log
(time ./bin/llama-perplexity --model ${model_q5_0} -f ${wiki_test} -t 1 -ngl 99 -c 2048 -b 512 --chunks 4 ) 2>&1 | tee -a $OUT/${ci}-tg-q5_0.log
(time ./bin/llama-perplexity --model ${model_q5_1} -f ${wiki_test} -t 1 -ngl 99 -c 2048 -b 512 --chunks 4 ) 2>&1 | tee -a $OUT/${ci}-tg-q5_1.log
(time ./bin/llama-perplexity --model ${model_q2_k} -f ${wiki_test} -t 1 -ngl 99 -c 2048 -b 512 --chunks 4 ) 2>&1 | tee -a $OUT/${ci}-tg-q2_k.log
(time ./bin/llama-perplexity --model ${model_q3_k} -f ${wiki_test} -t 1 -ngl 99 -c 2048 -b 512 --chunks 4 ) 2>&1 | tee -a $OUT/${ci}-tg-q3_k.log
(time ./bin/llama-perplexity --model ${model_q4_k} -f ${wiki_test} -t 1 -ngl 99 -c 2048 -b 512 --chunks 4 ) 2>&1 | tee -a $OUT/${ci}-tg-q4_k.log
(time ./bin/llama-perplexity --model ${model_q5_k} -f ${wiki_test} -t 1 -ngl 99 -c 2048 -b 512 --chunks 4 ) 2>&1 | tee -a $OUT/${ci}-tg-q5_k.log
(time ./bin/llama-perplexity --model ${model_q6_k} -f ${wiki_test} -t 1 -ngl 99 -c 2048 -b 512 --chunks 4 ) 2>&1 | tee -a $OUT/${ci}-tg-q6_k.log
(time ./bin/llama-imatrix --model ${model_f16} -f ${wiki_test} -t 1 -ngl 99 -c 2048 -b 512 --chunks 4 ) 2>&1 | tee -a $OUT/${ci}-imatrix.log
(time ./bin/llama-save-load-state --model ${model_q4_0} -ngl 10 -c 0 ) 2>&1 | tee -a $OUT/${ci}-save-load-state.log
(time ./bin/llama-save-load-state --model ${model_q4_0} -ngl 10 -c 0 -fa ) 2>&1 | tee -a $OUT/${ci}-save-load-state.log
(time ./bin/llama-save-load-state --model ${model_q4_0} -ngl 99 -c 0 ) 2>&1 | tee -a $OUT/${ci}-save-load-state.log
(time ./bin/llama-save-load-state --model ${model_q4_0} -ngl 99 -c 0 -fa ) 2>&1 | tee -a $OUT/${ci}-save-load-state.log
function check_ppl {
qnt="$1"
ppl=$(echo "$2" | grep -oE "[0-9]+\.[0-9]+" | tail -n 1)
if [ $(echo "$ppl > 20.0" | bc) -eq 1 ]; then
printf ' - %s @ %s (FAIL: ppl > 20.0)\n' "$qnt" "$ppl"
return 20
fi
printf ' - %s @ %s OK\n' "$qnt" "$ppl"
return 0
}
check_ppl "f16" "$(cat $OUT/${ci}-tg-f16.log | grep "^\[1\]")" | tee -a $OUT/${ci}-ppl.log
check_ppl "q8_0" "$(cat $OUT/${ci}-tg-q8_0.log | grep "^\[1\]")" | tee -a $OUT/${ci}-ppl.log
check_ppl "q4_0" "$(cat $OUT/${ci}-tg-q4_0.log | grep "^\[1\]")" | tee -a $OUT/${ci}-ppl.log
check_ppl "q4_1" "$(cat $OUT/${ci}-tg-q4_1.log | grep "^\[1\]")" | tee -a $OUT/${ci}-ppl.log
check_ppl "q5_0" "$(cat $OUT/${ci}-tg-q5_0.log | grep "^\[1\]")" | tee -a $OUT/${ci}-ppl.log
check_ppl "q5_1" "$(cat $OUT/${ci}-tg-q5_1.log | grep "^\[1\]")" | tee -a $OUT/${ci}-ppl.log
#check_ppl "q2_k" "$(cat $OUT/${ci}-tg-q2_k.log | grep "^\[1\]")" | tee -a $OUT/${ci}-ppl.log # note: ppl > 20.0 for this quant and model
check_ppl "q3_k" "$(cat $OUT/${ci}-tg-q3_k.log | grep "^\[1\]")" | tee -a $OUT/${ci}-ppl.log
check_ppl "q4_k" "$(cat $OUT/${ci}-tg-q4_k.log | grep "^\[1\]")" | tee -a $OUT/${ci}-ppl.log
check_ppl "q5_k" "$(cat $OUT/${ci}-tg-q5_k.log | grep "^\[1\]")" | tee -a $OUT/${ci}-ppl.log
check_ppl "q6_k" "$(cat $OUT/${ci}-tg-q6_k.log | grep "^\[1\]")" | tee -a $OUT/${ci}-ppl.log
cat $OUT/${ci}-imatrix.log | grep "Final" >> $OUT/${ci}-imatrix-sum.log
set +e
}
function gg_sum_pythia_2_8b {
gg_printf '### %s\n\n' "${ci}"
gg_printf 'Pythia 2.8B:\n'
gg_printf '- status: %s\n' "$(cat $OUT/${ci}.exit)"
gg_printf '- perplexity:\n%s\n' "$(cat $OUT/${ci}-ppl.log)"
gg_printf '- imatrix:\n```\n%s\n```\n' "$(cat $OUT/${ci}-imatrix-sum.log)"
gg_printf '- f16: \n```\n%s\n```\n' "$(cat $OUT/${ci}-tg-f16.log)"
gg_printf '- q8_0:\n```\n%s\n```\n' "$(cat $OUT/${ci}-tg-q8_0.log)"
gg_printf '- q4_0:\n```\n%s\n```\n' "$(cat $OUT/${ci}-tg-q4_0.log)"
gg_printf '- q4_1:\n```\n%s\n```\n' "$(cat $OUT/${ci}-tg-q4_1.log)"
@ -540,10 +720,8 @@ function gg_run_embd_bge_small {
./bin/llama-quantize ${model_f16} ${model_q8_0} q8_0
(time ./bin/llama-fit-params --model ${model_f16} 2>&1 | tee -a $OUT/${ci}-fp-f16.log)
(time ./bin/llama-embedding --model ${model_f16} -p "I believe the meaning of life is" -ngl 99 -c 0 --no-op-offload) 2>&1 | tee -a $OUT/${ci}-tg-f16.log
(time ./bin/llama-embedding --model ${model_q8_0} -p "I believe the meaning of life is" -ngl 99 -c 0 --no-op-offload) 2>&1 | tee -a $OUT/${ci}-tg-q8_0.log
(time ./bin/llama-embedding --model ${model_f16} -p "I believe the meaning of life is" -ngl 99 -c 0 ) 2>&1 | tee -a $OUT/${ci}-tg-f16.log
(time ./bin/llama-embedding --model ${model_q8_0} -p "I believe the meaning of life is" -ngl 99 -c 0 ) 2>&1 | tee -a $OUT/${ci}-tg-q8_0.log
set +e
}
@ -567,7 +745,12 @@ function gg_run_rerank_tiny {
gg_wget models-mnt/rerank-tiny/ https://huggingface.co/jinaai/jina-reranker-v1-tiny-en/raw/main/tokenizer_config.json
gg_wget models-mnt/rerank-tiny/ https://huggingface.co/jinaai/jina-reranker-v1-tiny-en/raw/main/special_tokens_map.json
gg_wget models-mnt/rerank-tiny/ https://huggingface.co/jinaai/jina-reranker-v1-tiny-en/resolve/main/pytorch_model.bin
gg_wget models-mnt/rerank-tiny/ https://huggingface.co/jinaai/jina-reranker-v1-tiny-en/raw/main/vocab.json
gg_wget models-mnt/rerank-tiny/ https://huggingface.co/jinaai/jina-reranker-v1-tiny-en/raw/main/sentence_bert_config.json
gg_wget models-mnt/rerank-tiny/ https://huggingface.co/jinaai/jina-reranker-v1-tiny-en/raw/main/vocab.txt
gg_wget models-mnt/rerank-tiny/ https://huggingface.co/jinaai/jina-reranker-v1-tiny-en/raw/main/modules.json
gg_wget models-mnt/rerank-tiny/ https://huggingface.co/jinaai/jina-reranker-v1-tiny-en/raw/main/config.json
gg_wget models-mnt/rerank-tiny/1_Pooling https://huggingface.co/jinaai/jina-reranker-v1-tiny-en/raw/main/1_Pooling/config.json
path_models="../models-mnt/rerank-tiny"
@ -582,10 +765,8 @@ function gg_run_rerank_tiny {
model_f16="${path_models}/ggml-model-f16.gguf"
(time ./bin/llama-fit-params --model ${model_f16} 2>&1 | tee -a $OUT/${ci}-fp-f16.log)
# for this model, the SEP token is "</s>"
(time ./bin/llama-embedding --model ${model_f16} -p "what is panda?\thi\nwhat is panda?\tit's a bear\nwhat is panda?\tThe giant panda (Ailuropoda melanoleuca), sometimes called a panda bear or simply panda, is a bear species endemic to China." -ngl 99 -c 0 --pooling rank --embd-normalize -1 --no-op-offload --verbose-prompt) 2>&1 | tee -a $OUT/${ci}-rk-f16.log
(time ./bin/llama-embedding --model ${model_f16} -p "what is panda?</s></s>hi\nwhat is panda?</s></s>it's a bear\nwhat is panda?</s></s>The giant panda (Ailuropoda melanoleuca), sometimes called a panda bear or simply panda, is a bear species endemic to China." -ngl 99 -c 0 --pooling rank --embd-normalize -1 --verbose-prompt) 2>&1 | tee -a $OUT/${ci}-rk-f16.log
# sample output
# rerank score 0: 0.029
@ -635,29 +816,6 @@ function gg_check_build_requirements {
fi
}
function gg_run_test_backend_ops_cpu {
cd ${SRC}
cd build-ci-release
set -e
(time ./bin/test-backend-ops -b CPU ) 2>&1 | tee -a $OUT/${ci}-test-backend-ops-cpu.log
set +e
}
function gg_sum_test_backend_ops_cpu {
gg_printf '### %s\n\n' "${ci}"
gg_printf 'Runs test-backend-ops for CPU backend\n'
gg_printf '- status: %s\n' "$(cat $OUT/${ci}.exit)"
gg_printf '```\n'
gg_printf '%s\n' "$(cat $OUT/${ci}-test-backend-ops-cpu.log)"
gg_printf '```\n'
gg_printf '\n'
}
## main
export LLAMA_LOG_PREFIX=1
@ -682,28 +840,35 @@ if [ -z ${GG_BUILD_LOW_PERF} ]; then
fi
ret=0
test $ret -eq 0 && gg_run ctest_debug
test $ret -eq 0 && gg_run ctest_release
if [ ! -z ${GG_BUILD_HIGH_PERF} ]; then
test $ret -eq 0 && gg_run test_backend_ops_cpu
if [ -z ${GG_BUILD_SYCL} ]; then
# SYCL build breaks with debug build flags
test $ret -eq 0 && gg_run ctest_debug
fi
test $ret -eq 0 && gg_run ctest_release
if [ -z ${GG_BUILD_LOW_PERF} ]; then
test $ret -eq 0 && gg_run embd_bge_small
test $ret -eq 0 && gg_run rerank_tiny
if [ -z ${GG_BUILD_CLOUD} ] || [ ${GG_BUILD_EXTRA_TESTS_0} ]; then
test $ret -eq 0 && gg_run test_scripts
if [ -z ${GG_BUILD_SYCL} ]; then
test $ret -eq 0 && gg_run test_scripts_debug
fi
test $ret -eq 0 && gg_run test_scripts_release
fi
test $ret -eq 0 && gg_run qwen3_0_6b
test $ret -eq 0 && gg_run ctest_with_model_debug
test $ret -eq 0 && gg_run ctest_with_model_release
if [ -z ${GG_BUILD_VRAM_GB} ] || [ ${GG_BUILD_VRAM_GB} -ge 8 ]; then
if [ -z ${GG_BUILD_CUDA} ] && [ -z ${GG_BUILD_VULKAN} ]; then
test $ret -eq 0 && gg_run pythia_1_4b
else
test $ret -eq 0 && gg_run pythia_2_8b
#test $ret -eq 0 && gg_run open_llama_7b_v2
fi
if [ -z ${GG_BUILD_SYCL} ]; then
test $ret -eq 0 && gg_run ctest_with_model_debug
fi
test $ret -eq 0 && gg_run ctest_with_model_release
fi
fi
cat $OUT/README.md
exit $ret

View File

@ -0,0 +1,6 @@
set( CMAKE_SYSTEM_NAME Windows )
set( CMAKE_SYSTEM_PROCESSOR arm64 )
set( target arm64-pc-windows-msvc )
set( CMAKE_C_COMPILER_TARGET ${target} )
set( CMAKE_CXX_COMPILER_TARGET ${target} )

View File

@ -39,10 +39,20 @@ if(Git_FOUND)
endif()
endif()
set(BUILD_COMPILER "${CMAKE_C_COMPILER_ID} ${CMAKE_C_COMPILER_VERSION}")
if(CMAKE_VS_PLATFORM_NAME)
if(MSVC)
set(BUILD_COMPILER "${CMAKE_C_COMPILER_ID} ${CMAKE_C_COMPILER_VERSION}")
set(BUILD_TARGET ${CMAKE_VS_PLATFORM_NAME})
else()
set(BUILD_TARGET "${CMAKE_SYSTEM_NAME} ${CMAKE_SYSTEM_PROCESSOR}")
execute_process(
COMMAND sh -c "\"$@\" --version | head -1" _ ${CMAKE_C_COMPILER}
OUTPUT_VARIABLE OUT
OUTPUT_STRIP_TRAILING_WHITESPACE
)
set(BUILD_COMPILER ${OUT})
execute_process(
COMMAND ${CMAKE_C_COMPILER} -dumpmachine
OUTPUT_VARIABLE OUT
OUTPUT_STRIP_TRAILING_WHITESPACE
)
set(BUILD_TARGET ${OUT})
endif()

View File

@ -32,27 +32,4 @@ function(llama_add_compile_flags)
set(CXX_FLAGS "" PARENT_SCOPE)
endif()
endif()
if (NOT MSVC)
if (LLAMA_SANITIZE_THREAD)
message(STATUS "Using -fsanitize=thread")
add_compile_options(-fsanitize=thread)
link_libraries (-fsanitize=thread)
endif()
if (LLAMA_SANITIZE_ADDRESS)
message(STATUS "Using -fsanitize=address")
add_compile_options(-fsanitize=address -fno-omit-frame-pointer)
link_libraries (-fsanitize=address)
endif()
if (LLAMA_SANITIZE_UNDEFINED)
message(STATUS "Using -fsanitize=undefined")
add_compile_options(-fsanitize=undefined)
link_libraries (-fsanitize=undefined)
endif()
endif()
endfunction()

View File

@ -1,21 +0,0 @@
get_filename_component(DEST_DIR "${DEST}" DIRECTORY)
file(MAKE_DIRECTORY "${DEST_DIR}")
if(NOT EXISTS "${DEST}")
message(STATUS "Downloading ${NAME} from ggml-org/models...")
endif()
file(DOWNLOAD
"https://huggingface.co/ggml-org/models/resolve/main/${NAME}?download=true"
"${DEST}"
TLS_VERIFY ON
EXPECTED_HASH ${HASH}
STATUS status
)
list(GET status 0 code)
if(NOT code EQUAL 0)
list(GET status 1 msg)
message(FATAL_ERROR "Failed to download ${NAME}: ${msg}")
endif()

View File

@ -1,40 +0,0 @@
define_property(GLOBAL PROPERTY LICENSE_TEXT
BRIEF_DOCS "Embedded licenses"
FULL_DOCS "Global string containing all aggregated licenses"
)
function(license_add_file NAME FILE)
if(NOT IS_ABSOLUTE "${FILE}")
set(FILE "${CMAKE_CURRENT_SOURCE_DIR}/${FILE}")
endif()
if(EXISTS "${FILE}")
set(TITLE "License for ${NAME}")
string(REGEX REPLACE "." "=" UNDERLINE "${TITLE}")
file(READ "${FILE}" TEXT)
get_property(TMP GLOBAL PROPERTY LICENSE_TEXT)
string(APPEND TMP "R\"=L=(${TITLE}\n${UNDERLINE}\n\n${TEXT})=L=\",\n")
set_property(GLOBAL PROPERTY LICENSE_TEXT "${TMP}")
else()
message(WARNING "License file '${FILE}' not found")
endif()
endfunction()
function(license_generate TARGET_NAME)
message(STATUS "Generating embedded license file for target: ${TARGET_NAME}")
get_property(TEXT GLOBAL PROPERTY LICENSE_TEXT)
set(CPP_CONTENT "// Generated by CMake\n\n")
string(APPEND CPP_CONTENT "const char* LICENSES[] = {\n")
string(APPEND CPP_CONTENT "${TEXT}")
string(APPEND CPP_CONTENT "nullptr\n")
string(APPEND CPP_CONTENT "};\n")
set(CPP_FILE "${CMAKE_BINARY_DIR}/license.cpp")
file(WRITE "${CPP_FILE}" "${CPP_CONTENT}")
if(TARGET ${TARGET_NAME})
target_sources(${TARGET_NAME} PRIVATE "${CPP_FILE}")
else()
message(FATAL_ERROR "Target '${TARGET_NAME}' does not exist")
endif()
endfunction()

View File

@ -1,29 +0,0 @@
set(CMAKE_SYSTEM_NAME Linux)
set(CMAKE_SYSTEM_PROCESSOR riscv64)
set(CMAKE_SYSTEM_VERSION 1)
if (CMAKE_HOST_SYSTEM_PROCESSOR MATCHES "^(riscv)")
message(STATUS "HOST SYSTEM ${CMAKE_HOST_SYSTEM_PROCESSOR}")
else()
set(GNU_MACHINE riscv64-unknown-linux-gnu CACHE STRING "GNU compiler triple")
if (DEFINED ENV{RISCV_ROOT_PATH})
file(TO_CMAKE_PATH $ENV{RISCV_ROOT_PATH} RISCV_ROOT_PATH)
else()
message(FATAL_ERROR "RISCV_ROOT_PATH env must be defined")
endif()
set(RISCV_ROOT_PATH ${RISCV_ROOT_PATH} CACHE STRING "root path to riscv toolchain")
set(CMAKE_C_COMPILER ${RISCV_ROOT_PATH}/bin/riscv64-unknown-linux-gnu-gcc)
set(CMAKE_CXX_COMPILER ${RISCV_ROOT_PATH}/bin/riscv64-unknown-linux-gnu-g++)
set(CMAKE_STRIP ${RISCV_ROOT_PATH}/bin/riscv64-unknown-linux-gnu-strip)
set(CMAKE_FIND_ROOT_PATH "${RISCV_ROOT_PATH}/riscv64-unknown-linux-gnu")
set(CMAKE_SYSROOT "${RISCV_ROOT_PATH}/sysroot")
endif()
set(CMAKE_FIND_ROOT_PATH_MODE_PROGRAM NEVER)
set(CMAKE_FIND_ROOT_PATH_MODE_LIBRARY ONLY)
set(CMAKE_FIND_ROOT_PATH_MODE_INCLUDE ONLY)
set(CMAKE_FIND_ROOT_PATH_MODE_PACKAGE ONLY)
set(CMAKE_C_FLAGS "-march=rv64gcv_zfh_zba_zicbop -mabi=lp64d ${CMAKE_C_FLAGS}")
set(CMAKE_CXX_FLAGS "-march=rv64gcv_zfh_zba_zicbop -mabi=lp64d ${CXX_FLAGS}")
set(CMAKE_EXE_LINKER_FLAGS "${CMAKE_EXE_LINKER_FLAGS} -latomic")

View File

@ -3,3 +3,9 @@ set( CMAKE_SYSTEM_PROCESSOR x86_64 )
set( CMAKE_C_COMPILER clang )
set( CMAKE_CXX_COMPILER clang++ )
set( arch_c_flags "-march=native" )
set( CMAKE_C_FLAGS_INIT "${arch_c_flags}" )
set( CMAKE_CXX_FLAGS_INIT "${arch_c_flags}" )

View File

@ -7,8 +7,8 @@ llama_add_compile_flags()
# Build info header
#
if(EXISTS "${PROJECT_SOURCE_DIR}/.git")
set(GIT_DIR "${PROJECT_SOURCE_DIR}/.git")
if(EXISTS "${CMAKE_CURRENT_SOURCE_DIR}/../.git")
set(GIT_DIR "${CMAKE_CURRENT_SOURCE_DIR}/../.git")
# Is git submodule
if(NOT IS_DIRECTORY "${GIT_DIR}")
@ -18,26 +18,34 @@ if(EXISTS "${PROJECT_SOURCE_DIR}/.git")
if (SLASH_POS EQUAL 0)
set(GIT_DIR "${REAL_GIT_DIR}")
else()
set(GIT_DIR "${PROJECT_SOURCE_DIR}/${REAL_GIT_DIR}")
set(GIT_DIR "${CMAKE_CURRENT_SOURCE_DIR}/../${REAL_GIT_DIR}")
endif()
endif()
if(EXISTS "${GIT_DIR}/index")
# For build-info.cpp below
set_property(DIRECTORY APPEND PROPERTY CMAKE_CONFIGURE_DEPENDS "${GIT_DIR}/index")
set(GIT_INDEX "${GIT_DIR}/index")
else()
message(WARNING "Git index not found in git repository.")
set(GIT_INDEX "")
endif()
else()
message(WARNING "Git repository not found; to enable automatic generation of build info, make sure Git is installed and the project is a Git repository.")
set(GIT_INDEX "")
endif()
set(TEMPLATE_FILE "${CMAKE_CURRENT_SOURCE_DIR}/build-info.cpp.in")
set(OUTPUT_FILE "${CMAKE_CURRENT_BINARY_DIR}/build-info.cpp")
configure_file(${TEMPLATE_FILE} ${OUTPUT_FILE})
# Add a custom command to rebuild build-info.cpp when .git/index changes
add_custom_command(
OUTPUT "${CMAKE_CURRENT_SOURCE_DIR}/build-info.cpp"
COMMENT "Generating build details from Git"
COMMAND ${CMAKE_COMMAND} -DMSVC=${MSVC} -DCMAKE_C_COMPILER_VERSION=${CMAKE_C_COMPILER_VERSION}
-DCMAKE_C_COMPILER_ID=${CMAKE_C_COMPILER_ID} -DCMAKE_VS_PLATFORM_NAME=${CMAKE_VS_PLATFORM_NAME}
-DCMAKE_C_COMPILER=${CMAKE_C_COMPILER} -P "${CMAKE_CURRENT_SOURCE_DIR}/cmake/build-info-gen-cpp.cmake"
WORKING_DIRECTORY "${CMAKE_CURRENT_SOURCE_DIR}/.."
DEPENDS "${CMAKE_CURRENT_SOURCE_DIR}/build-info.cpp.in" ${GIT_INDEX}
VERBATIM
)
set(TARGET build_info)
add_library(${TARGET} OBJECT ${OUTPUT_FILE})
add_library(${TARGET} OBJECT build-info.cpp)
if (BUILD_SHARED_LIBS)
set_target_properties(${TARGET} PROPERTIES POSITION_INDEPENDENT_CODE ON)
endif()
@ -48,75 +56,44 @@ add_library(${TARGET} STATIC
arg.cpp
arg.h
base64.hpp
chat-parser.cpp
chat-parser.h
chat-parser-xml-toolcall.h
chat-parser-xml-toolcall.cpp
chat-peg-parser.cpp
chat-peg-parser.h
chat.cpp
chat.h
common.cpp
common.h
console.cpp
console.h
debug.cpp
debug.h
download.cpp
download.h
http.h
json-partial.cpp
json-partial.h
json-schema-to-grammar.cpp
json.hpp
llguidance.cpp
log.cpp
log.h
minja/chat-template.hpp
minja/minja.hpp
ngram-cache.cpp
ngram-cache.h
ngram-map.cpp
ngram-map.h
ngram-mod.cpp
ngram-mod.h
peg-parser.cpp
peg-parser.h
preset.cpp
preset.h
regex-partial.cpp
regex-partial.h
sampling.cpp
sampling.h
speculative.cpp
speculative.h
unicode.cpp
unicode.h
jinja/lexer.cpp
jinja/lexer.h
jinja/parser.cpp
jinja/parser.h
jinja/runtime.cpp
jinja/runtime.h
jinja/value.cpp
jinja/value.h
jinja/string.cpp
jinja/string.h
jinja/caps.cpp
jinja/caps.h
)
target_include_directories(${TARGET} PUBLIC . ../vendor)
target_compile_features (${TARGET} PUBLIC cxx_std_17)
if (BUILD_SHARED_LIBS)
set_target_properties(${TARGET} PROPERTIES POSITION_INDEPENDENT_CODE ON)
endif()
# TODO: use list(APPEND LLAMA_COMMON_EXTRA_LIBS ...)
set(LLAMA_COMMON_EXTRA_LIBS build_info)
if (LLAMA_HTTPLIB)
target_compile_definitions(${TARGET} PUBLIC LLAMA_USE_HTTPLIB)
set(LLAMA_COMMON_EXTRA_LIBS ${LLAMA_COMMON_EXTRA_LIBS} cpp-httplib)
endif()
# Use curl to download model url
if (LLAMA_CURL)
find_package(CURL)
if (NOT CURL_FOUND)
message(FATAL_ERROR "Could NOT find CURL. Hint: to disable this feature, set -DLLAMA_CURL=OFF")
endif()
target_compile_definitions(${TARGET} PUBLIC LLAMA_USE_CURL)
include_directories(${CURL_INCLUDE_DIRS})
find_library(CURL_LIBRARY curl REQUIRED)
set(LLAMA_COMMON_EXTRA_LIBS ${LLAMA_COMMON_EXTRA_LIBS} ${CURL_LIBRARY})
endif ()
if (LLAMA_LLGUIDANCE)
include(ExternalProject)
@ -140,13 +117,13 @@ if (LLAMA_LLGUIDANCE)
ExternalProject_Add(llguidance_ext
GIT_REPOSITORY https://github.com/guidance-ai/llguidance
# v1.0.1:
GIT_TAG d795912fedc7d393de740177ea9ea761e7905774
# v0.7.10:
GIT_TAG 0309d2a6bf40abda35344a362edc71e06d5009f8
PREFIX ${CMAKE_BINARY_DIR}/llguidance
SOURCE_DIR ${LLGUIDANCE_SRC}
BUILD_IN_SOURCE TRUE
CONFIGURE_COMMAND ""
BUILD_COMMAND cargo build --release --package llguidance
BUILD_COMMAND cargo build --release
INSTALL_COMMAND ""
BUILD_BYPRODUCTS ${LLGUIDANCE_PATH}/${LLGUIDANCE_LIB_NAME} ${LLGUIDANCE_PATH}/llguidance.h
UPDATE_COMMAND ""
@ -162,4 +139,6 @@ if (LLAMA_LLGUIDANCE)
set(LLAMA_COMMON_EXTRA_LIBS ${LLAMA_COMMON_EXTRA_LIBS} llguidance ${LLGUIDANCE_PLATFORM_LIBS})
endif ()
target_link_libraries(${TARGET} PRIVATE ${LLAMA_COMMON_EXTRA_LIBS} PUBLIC llama Threads::Threads)
target_include_directories(${TARGET} PUBLIC .)
target_compile_features (${TARGET} PUBLIC cxx_std_17)
target_link_libraries (${TARGET} PRIVATE ${LLAMA_COMMON_EXTRA_LIBS} PUBLIC llama Threads::Threads)

File diff suppressed because it is too large Load Diff

View File

@ -3,14 +3,8 @@
#include "common.h"
#include <set>
#include <map>
#include <string>
#include <vector>
#include <cstring>
// pseudo-env variable to identify preset-only arguments
#define COMMON_ARG_PRESET_LOAD_ON_STARTUP "__PRESET_LOAD_ON_STARTUP"
#define COMMON_ARG_PRESET_STOP_TIMEOUT "__PRESET_STOP_TIMEOUT"
//
// CLI argument parsing
@ -20,20 +14,15 @@ struct common_arg {
std::set<enum llama_example> examples = {LLAMA_EXAMPLE_COMMON};
std::set<enum llama_example> excludes = {};
std::vector<const char *> args;
std::vector<const char *> args_neg; // for negated args like --no-xxx
const char * value_hint = nullptr; // help text or example for arg value
const char * value_hint_2 = nullptr; // for second arg value
const char * env = nullptr;
std::string help;
bool is_sparam = false; // is current arg a sampling param?
bool is_preset_only = false; // is current arg preset-only (not treated as CLI arg)
void (*handler_void) (common_params & params) = nullptr;
void (*handler_string) (common_params & params, const std::string &) = nullptr;
void (*handler_str_str)(common_params & params, const std::string &, const std::string &) = nullptr;
void (*handler_int) (common_params & params, int) = nullptr;
void (*handler_bool) (common_params & params, bool) = nullptr;
common_arg() = default;
common_arg(
const std::initializer_list<const char *> & args,
@ -55,13 +44,6 @@ struct common_arg {
void (*handler)(common_params & params)
) : args(args), help(help), handler_void(handler) {}
common_arg(
const std::initializer_list<const char *> & args,
const std::initializer_list<const char *> & args_neg,
const std::string & help,
void (*handler)(common_params & params, bool)
) : args(args), args_neg(args_neg), help(help), handler_bool(handler) {}
// support 2 values for arg
common_arg(
const std::initializer_list<const char *> & args,
@ -75,38 +57,13 @@ struct common_arg {
common_arg & set_excludes(std::initializer_list<enum llama_example> excludes);
common_arg & set_env(const char * env);
common_arg & set_sparam();
common_arg & set_preset_only();
bool in_example(enum llama_example ex);
bool is_exclude(enum llama_example ex);
bool get_value_from_env(std::string & output) const;
bool has_value_from_env() const;
std::string to_string() const;
// for using as key in std::map
bool operator<(const common_arg& other) const {
if (args.empty() || other.args.empty()) {
return false;
}
return strcmp(args[0], other.args[0]) < 0;
}
bool operator==(const common_arg& other) const {
if (args.empty() || other.args.empty()) {
return false;
}
return strcmp(args[0], other.args[0]) == 0;
}
// get all args and env vars (including negated args/env)
std::vector<std::string> get_args() const;
std::vector<std::string> get_env() const;
bool get_value_from_env(std::string & output);
bool has_value_from_env();
std::string to_string();
};
namespace common_arg_utils {
bool is_truthy(const std::string & value);
bool is_falsey(const std::string & value);
bool is_autoy(const std::string & value);
}
struct common_params_context {
enum llama_example ex = LLAMA_EXAMPLE_COMMON;
common_params & params;
@ -119,13 +76,14 @@ struct common_params_context {
// if one argument has invalid value, it will automatically display usage of the specific argument (and not the full usage message)
bool common_params_parse(int argc, char ** argv, common_params & params, llama_example ex, void(*print_usage)(int, char **) = nullptr);
// parse input arguments from CLI into a map
bool common_params_to_map(int argc, char ** argv, llama_example ex, std::map<common_arg, std::string> & out_map);
// populate preset-only arguments
// these arguments are not treated as command line arguments
// see: https://github.com/ggml-org/llama.cpp/issues/18163
void common_params_add_preset_options(std::vector<common_arg> & args);
// initialize argument parser context - used by test-arg-parser and preset
// function to be used by test-arg-parser
common_params_context common_params_parser_init(common_params & params, llama_example ex, void(*print_usage)(int, char **) = nullptr);
bool common_has_curl();
struct common_remote_params {
std::vector<std::string> headers;
long timeout = 0; // CURLOPT_TIMEOUT, in seconds ; 0 means no timeout
long max_size = 0; // max size of the response ; unlimited if 0 ; max is 2GB
};
// get remote file content, returns <http_code, raw_response_body>
std::pair<long, std::vector<char>> common_remote_get_content(const std::string & url, const common_remote_params & params);

View File

@ -1,4 +1,4 @@
int LLAMA_BUILD_NUMBER = @LLAMA_BUILD_NUMBER@;
char const *LLAMA_COMMIT = "@LLAMA_BUILD_COMMIT@";
int LLAMA_BUILD_NUMBER = @BUILD_NUMBER@;
char const *LLAMA_COMMIT = "@BUILD_COMMIT@";
char const *LLAMA_COMPILER = "@BUILD_COMPILER@";
char const *LLAMA_BUILD_TARGET = "@BUILD_TARGET@";

View File

@ -1,879 +0,0 @@
#include "chat.h"
#include "chat-parser.h"
#include "common.h"
#include "json-partial.h"
#include "json-schema-to-grammar.h"
#include "log.h"
#include "regex-partial.h"
using json = nlohmann::ordered_json;
class xml_toolcall_syntax_exception : public std::runtime_error {
public:
xml_toolcall_syntax_exception(const std::string & message) : std::runtime_error(message) {}
};
template<typename T>
inline void sort_uniq(std::vector<T> &vec) {
std::sort(vec.begin(), vec.end());
vec.erase(std::unique(vec.begin(), vec.end()), vec.end());
}
template<typename T>
inline bool all_space(const T &str) {
return std::all_of(str.begin(), str.end(), [](unsigned char ch) { return std::isspace(ch); });
}
static size_t utf8_truncate_safe(const std::string_view s) {
size_t len = s.size();
if (len == 0) return 0;
size_t i = len;
for (size_t back = 0; back < 4 && i > 0; ++back) {
--i;
unsigned char c = s[i];
if ((c & 0x80) == 0) {
return len;
} else if ((c & 0xC0) == 0xC0) {
size_t expected_len = 0;
if ((c & 0xE0) == 0xC0) expected_len = 2;
else if ((c & 0xF0) == 0xE0) expected_len = 3;
else if ((c & 0xF8) == 0xF0) expected_len = 4;
else return i;
if (len - i >= expected_len) {
return len;
} else {
return i;
}
}
}
return len - std::min(len, size_t(3));
}
inline void utf8_truncate_safe_resize(std::string &s) {
s.resize(utf8_truncate_safe(s));
}
inline std::string_view utf8_truncate_safe_view(const std::string_view s) {
return s.substr(0, utf8_truncate_safe(s));
}
static std::optional<common_chat_msg_parser::find_regex_result> try_find_2_literal_splited_by_spaces(common_chat_msg_parser & builder, const std::string & literal1, const std::string & literal2) {
if (literal1.size() == 0) return builder.try_find_literal(literal2);
const auto saved_pos = builder.pos();
while (auto res = builder.try_find_literal(literal1)) {
builder.consume_spaces();
const auto match_len = std::min(literal2.size(), builder.input().size() - builder.pos());
if (builder.input().compare(builder.pos(), match_len, literal2, 0, match_len) == 0) {
if (res->prelude.size() != res->groups[0].begin - saved_pos) {
res->prelude = builder.str({saved_pos, res->groups[0].begin});
}
builder.move_to(builder.pos() + match_len);
res->groups[0].end = builder.pos();
GGML_ASSERT(res->groups[0].begin != res->groups[0].end);
return res;
}
builder.move_to(res->groups[0].begin + 1);
}
builder.move_to(saved_pos);
return std::nullopt;
}
/**
* make a GBNF that accept any strings except those containing any of the forbidden strings.
*/
std::string make_gbnf_excluding(std::vector<std::string> forbids) {
constexpr auto charclass_escape = [](unsigned char c) -> std::string {
if (c == '\\' || c == ']' || c == '^' || c == '-') {
std::string s = "\\";
s.push_back((char)c);
return s;
}
if (isprint(c)) {
return std::string(1, (char)c);
}
char buf[16];
snprintf(buf, 15, "\\x%02X", c);
return std::string(buf);
};
constexpr auto build_expr = [charclass_escape](auto self, const std::vector<std::string>& forbids, int l, int r, int depth) -> std::string {
std::vector<std::pair<unsigned char, std::pair<int,int>>> children;
int i = l;
while (i < r) {
const std::string &s = forbids[i];
if ((int)s.size() == depth) {
++i;
continue;
}
unsigned char c = (unsigned char)s[depth];
int j = i;
while (j < r && (int)forbids[j].size() > depth &&
(unsigned char)forbids[j][depth] == c) {
++j;
}
children.push_back({c, {i, j}});
i = j;
}
std::vector<std::string> alts;
if (!children.empty()) {
std::string cls;
for (auto &ch : children) cls += charclass_escape(ch.first);
alts.push_back(std::string("[^") + cls + "]");
}
for (auto &ch : children) {
std::string childExpr = self(self, forbids, ch.second.first, ch.second.second, depth+1);
if (!childExpr.empty()) {
std::string quoted_ch = "\"";
if (ch.first == '\\') quoted_ch += "\\\\";
else if (ch.first == '"') quoted_ch += "\\\"";
else if (isprint(ch.first)) quoted_ch.push_back(ch.first);
else {
char buf[16];
snprintf(buf, 15, "\\x%02X", ch.first);
quoted_ch += buf;
}
quoted_ch += "\"";
std::string branch = quoted_ch + std::string(" ") + childExpr;
alts.push_back(branch);
}
}
if (alts.empty()) return "";
std::ostringstream oss;
oss << "( ";
for (size_t k = 0; k < alts.size(); ++k) {
if (k) oss << " | ";
oss << alts[k];
}
oss << " )";
return oss.str();
};
if (forbids.empty()) return "( . )*";
sort(forbids.begin(), forbids.end());
std::string expr = build_expr(build_expr, forbids, 0, forbids.size(), 0);
if (expr.empty()) {
std::string cls;
for (auto &s : forbids) if (!s.empty()) cls += charclass_escape((unsigned char)s[0]);
expr = std::string("( [^") + cls + "] )";
}
if (forbids.size() == 1)
return expr + "*";
else
return std::string("( ") + expr + " )*";
}
/**
* Build grammar for xml-style tool call
* form.scope_start and form.scope_end can be empty.
* Requires data.format for model-specific hacks.
*/
void build_grammar_xml_tool_call(common_chat_params & data, const json & tools, const struct xml_tool_call_format & form) {
GGML_ASSERT(!form.tool_start.empty());
GGML_ASSERT(!form.tool_sep.empty());
GGML_ASSERT(!form.key_start.empty());
GGML_ASSERT(!form.val_end.empty());
GGML_ASSERT(!form.tool_end.empty());
std::string key_val_sep = form.key_val_sep;
if (form.key_val_sep2) {
key_val_sep += "\n";
key_val_sep += *form.key_val_sep2;
}
GGML_ASSERT(!key_val_sep.empty());
if (tools.is_array() && !tools.empty()) {
data.grammar = build_grammar([&](const common_grammar_builder &builder) {
auto string_arg_val = form.last_val_end ?
builder.add_rule("string-arg-val", make_gbnf_excluding({form.val_end, *form.last_val_end})) :
builder.add_rule("string-arg-val", make_gbnf_excluding({form.val_end}));
std::vector<std::string> tool_rules;
for (const auto & tool : tools) {
if (!tool.contains("type") || tool.at("type") != "function" || !tool.contains("function")) {
LOG_WRN("Skipping tool without function: %s", tool.dump(2).c_str());
continue;
}
const auto & function = tool.at("function");
if (!function.contains("name") || !function.at("name").is_string()) {
LOG_WRN("Skipping invalid function (invalid name): %s", function.dump(2).c_str());
continue;
}
if (!function.contains("parameters") || !function.at("parameters").is_object()) {
LOG_WRN("Skipping invalid function (invalid parameters): %s", function.dump(2).c_str());
continue;
}
std::string name = function.at("name");
auto parameters = function.at("parameters");
builder.resolve_refs(parameters);
struct parameter_rule {
std::string symbol_name;
bool is_required;
};
std::vector<parameter_rule> arg_rules;
if (!parameters.contains("properties") || !parameters.at("properties").is_object()) {
LOG_WRN("Skipping invalid function (invalid properties): %s", function.dump(2).c_str());
continue;
} else {
std::vector<std::string> requiredParameters;
if (parameters.contains("required")) {
try { parameters.at("required").get_to(requiredParameters); }
catch (const std::runtime_error&) {
LOG_WRN("Invalid function required parameters, ignoring: %s", function.at("required").dump(2).c_str());
}
}
sort_uniq(requiredParameters);
for (const auto & [key, value] : parameters.at("properties").items()) {
std::string quoted_key = key;
bool required = std::binary_search(requiredParameters.begin(), requiredParameters.end(), key);
if (form.key_start.back() == '"' && key_val_sep[0] == '"') {
quoted_key = gbnf_format_literal(key);
quoted_key = quoted_key.substr(1, quoted_key.size() - 2);
}
arg_rules.push_back(parameter_rule {builder.add_rule("func-" + name + "-kv-" + key,
gbnf_format_literal(form.key_start) + " " +
gbnf_format_literal(quoted_key) + " " +
gbnf_format_literal(key_val_sep) + " " +
((value.contains("type") && value["type"].is_string() && value["type"] == "string" && (!form.raw_argval || *form.raw_argval)) ?
(form.raw_argval ?
string_arg_val :
"( " + string_arg_val + " | " + builder.add_schema(name + "-arg-" + key, value) + " )"
) :
builder.add_schema(name + "-arg-" + key, value)
)
), required});
}
}
auto next_arg_with_sep = builder.add_rule(name + "-last-arg-end", form.last_val_end ? gbnf_format_literal(*form.last_val_end) : gbnf_format_literal(form.val_end));
decltype(next_arg_with_sep) next_arg = "\"\"";
for (auto i = arg_rules.size() - 1; /* i >= 0 && */ i < arg_rules.size(); --i) {
std::string include_this_arg = arg_rules[i].symbol_name + " " + next_arg_with_sep;
next_arg = builder.add_rule(name + "-arg-after-" + std::to_string(i), arg_rules[i].is_required ?
include_this_arg : "( " + include_this_arg + " ) | " + next_arg
);
include_this_arg = gbnf_format_literal(form.val_end) + " " + include_this_arg;
next_arg_with_sep = builder.add_rule(name + "-arg-after-" + std::to_string(i) + "-with-sep", arg_rules[i].is_required ?
include_this_arg : "( " + include_this_arg + " ) | " + next_arg_with_sep
);
}
std::string quoted_name = name;
if (form.tool_start.back() == '"' && form.tool_sep[0] == '"') {
quoted_name = gbnf_format_literal(name);
quoted_name = quoted_name.substr(1, quoted_name.size() - 2);
}
quoted_name = gbnf_format_literal(quoted_name);
// Kimi-K2 uses functions.{{ tool_call['function']['name'] }}:{{ loop.index }} as function name
if (data.format == COMMON_CHAT_FORMAT_KIMI_K2) {
quoted_name = "\"functions.\" " + quoted_name + " \":\" [0-9]+";
}
tool_rules.push_back(builder.add_rule(name + "-call",
gbnf_format_literal(form.tool_start) + " " +
quoted_name + " " +
gbnf_format_literal(form.tool_sep) + " " +
next_arg
));
}
auto tool_call_once = builder.add_rule("root-tool-call-once", string_join(tool_rules, " | "));
auto tool_call_more = builder.add_rule("root-tool-call-more", gbnf_format_literal(form.tool_end) + " " + tool_call_once);
auto call_end = builder.add_rule("root-call-end", form.last_tool_end ? gbnf_format_literal(*form.last_tool_end) : gbnf_format_literal(form.tool_end));
auto tool_call_multiple_with_end = builder.add_rule("root-tool-call-multiple-with-end", tool_call_once + " " + tool_call_more + "* " + call_end);
builder.add_rule("root",
(form.scope_start.empty() ? "" : gbnf_format_literal(form.scope_start) + " ") +
tool_call_multiple_with_end + "?" +
(form.scope_end.empty() ? "" : " " + gbnf_format_literal(form.scope_end))
);
});
// grammar trigger for tool call
data.grammar_triggers.push_back({ COMMON_GRAMMAR_TRIGGER_TYPE_WORD, form.scope_start + form.tool_start });
}
}
/**
* Parse XML-Style tool call for given xml_tool_call_format. Return false for invalid syntax and get the position untouched.
* Throws xml_toolcall_syntax_exception if there is invalid syntax and cannot recover the original status for common_chat_msg_parser.
* form.scope_start, form.tool_sep and form.scope_end can be empty.
*/
inline bool parse_xml_tool_calls(common_chat_msg_parser & builder, const struct xml_tool_call_format & form) {
GGML_ASSERT(!form.tool_start.empty());
GGML_ASSERT(!form.key_start.empty());
GGML_ASSERT(!form.key_val_sep.empty());
GGML_ASSERT(!form.val_end.empty());
GGML_ASSERT(!form.tool_end.empty());
// Helper to choose return false or throw error
constexpr auto return_error = [](common_chat_msg_parser & builder, auto &start_pos, const bool &recovery) {
LOG_DBG("Failed to parse XML-Style tool call at position: %s\n", gbnf_format_literal(builder.consume_rest().substr(0, 20)).c_str());
if (recovery) {
builder.move_to(start_pos);
return false;
} else throw xml_toolcall_syntax_exception("Tool call parsing failed with unrecoverable errors. Try using a grammar to constrain the models output.");
};
// Drop substring from needle to end from a JSON
constexpr auto partial_json = [](std::string &json_str, std::string_view needle = "XML_TOOL_CALL_PARTIAL_FLAG") {
auto pos = json_str.rfind(needle);
if (pos == std::string::npos) {
return false;
}
for (auto i = pos + needle.size(); i < json_str.size(); ++i) {
unsigned char ch = static_cast<unsigned char>(json_str[i]);
if (ch != '\'' && ch != '"' && ch != '}' && ch != ':' && !std::isspace(ch)) {
return false;
}
}
if (pos != 0 && json_str[pos - 1] == '"') {
--pos;
}
json_str.resize(pos);
return true;
};
// Helper to generate a partial argument JSON
constexpr auto gen_partial_json = [partial_json](auto set_partial_arg, auto &arguments, auto &builder, auto &function_name) {
auto rest = builder.consume_rest();
utf8_truncate_safe_resize(rest);
set_partial_arg(rest, "XML_TOOL_CALL_PARTIAL_FLAG");
auto tool_str = arguments.dump();
if (partial_json(tool_str)) {
if (builder.add_tool_call(function_name, "", tool_str)) {
return;
}
}
LOG_DBG("Failed to parse partial XML-Style tool call, fallback to non-partial: %s\n", tool_str.c_str());
};
// Helper to find a close (because there may be form.last_val_end or form.last_tool_end)
constexpr auto try_find_close = [](
common_chat_msg_parser & builder,
const std::string & end,
const std::optional<std::string> & alt_end,
const std::string & end_next,
const std::optional<std::string> & alt_end_next
) {
auto saved_pos = builder.pos();
auto tc = builder.try_find_literal(end);
auto val_end_size = end.size();
if (alt_end) {
auto pos_1 = builder.pos();
builder.move_to(saved_pos);
auto tc2 = try_find_2_literal_splited_by_spaces(builder, *alt_end, end_next);
if (alt_end_next) {
builder.move_to(saved_pos);
auto tc3 = try_find_2_literal_splited_by_spaces(builder, *alt_end, *alt_end_next);
if (tc3 && (!tc2 || tc2->prelude.size() > tc3->prelude.size())) {
tc2 = tc3;
}
}
if (tc2 && (!tc || tc->prelude.size() > tc2->prelude.size())) {
tc = tc2;
tc->groups[0].end = std::min(builder.input().size(), tc->groups[0].begin + alt_end->size());
builder.move_to(tc->groups[0].end);
val_end_size = alt_end->size();
} else {
builder.move_to(pos_1);
}
}
return std::make_pair(val_end_size, tc);
};
// Helper to find a val_end or last_val_end, returns matched pattern size
const auto try_find_val_end = [try_find_close, &builder, &form]() {
return try_find_close(builder, form.val_end, form.last_val_end, form.tool_end, form.last_tool_end);
};
// Helper to find a tool_end or last_tool_end, returns matched pattern size
const auto try_find_tool_end = [try_find_close, &builder, &form]() {
return try_find_close(builder, form.tool_end, form.last_tool_end, form.scope_end, std::nullopt);
};
bool recovery = true;
const auto start_pos = builder.pos();
if (!all_space(form.scope_start)) {
if (auto tc = builder.try_find_literal(form.scope_start)) {
if (all_space(tc->prelude)) {
if (form.scope_start.size() != tc->groups[0].end - tc->groups[0].begin)
throw common_chat_msg_partial_exception("Partial literal: " + gbnf_format_literal(form.scope_start));
} else {
builder.move_to(start_pos);
return false;
}
} else return false;
}
while (auto tc = builder.try_find_literal(form.tool_start)) {
if (!all_space(tc->prelude)) {
LOG_DBG("XML-Style tool call: Expected %s, but found %s, trying to match next pattern\n",
gbnf_format_literal(form.tool_start).c_str(),
gbnf_format_literal(tc->prelude).c_str()
);
builder.move_to(tc->groups[0].begin - tc->prelude.size());
break;
}
// Find tool name
auto func_name = builder.try_find_literal(all_space(form.tool_sep) ? form.key_start : form.tool_sep);
if (!func_name) {
auto [sz, tc] = try_find_tool_end();
func_name = tc;
}
if (!func_name) {
// Partial tool name not supported
throw common_chat_msg_partial_exception("incomplete tool_call");
}
// If the model generate multiple tool call and the first tool call has no argument
if (func_name->prelude.find(form.tool_end) != std::string::npos || (form.last_tool_end ? func_name->prelude.find(*form.last_tool_end) != std::string::npos : false)) {
builder.move_to(func_name->groups[0].begin - func_name->prelude.size());
auto [sz, tc] = try_find_tool_end();
func_name = tc;
}
// Parse tool name
builder.move_to(all_space(form.tool_sep) ? func_name->groups[0].begin : func_name->groups[0].end);
std::string function_name = string_strip(func_name->prelude);
// Kimi-K2 uses functions.{{ tool_call['function']['name'] }}:{{ loop.index }} as function name
if (builder.syntax().format == COMMON_CHAT_FORMAT_KIMI_K2) {
if (string_starts_with(function_name, "functions.")) {
static const std::regex re(":\\d+$");
if (std::regex_search(function_name, re)) {
function_name = function_name.substr(10, function_name.rfind(":") - 10);
}
}
}
// Argument JSON
json arguments = json::object();
// Helper to generate a partial argument JSON
const auto gen_partial_args = [&](auto set_partial_arg) {
gen_partial_json(set_partial_arg, arguments, builder, function_name);
};
// Parse all arg_key/arg_value pairs
while (auto tc = builder.try_find_literal(form.key_start)) {
if (!all_space(tc->prelude)) {
LOG_DBG("XML-Style tool call: Expected %s, but found %s, trying to match next pattern\n",
gbnf_format_literal(form.key_start).c_str(),
gbnf_format_literal(tc->prelude).c_str()
);
builder.move_to(tc->groups[0].begin - tc->prelude.size());
break;
}
if (tc->groups[0].end - tc->groups[0].begin != form.key_start.size()) {
auto tool_call_arg = arguments.dump();
if (tool_call_arg.size() != 0 && tool_call_arg[tool_call_arg.size() - 1] == '}') {
tool_call_arg.resize(tool_call_arg.size() - 1);
}
builder.add_tool_call(function_name, "", tool_call_arg);
throw common_chat_msg_partial_exception("Partial literal: " + gbnf_format_literal(form.key_start));
}
// Parse arg_key
auto key_res = builder.try_find_literal(form.key_val_sep);
if (!key_res) {
gen_partial_args([&](auto &rest, auto &needle) {arguments[rest + needle] = "";});
throw common_chat_msg_partial_exception("Expected " + gbnf_format_literal(form.key_val_sep) + " after " + gbnf_format_literal(form.key_start));
}
if (key_res->groups[0].end - key_res->groups[0].begin != form.key_val_sep.size()) {
gen_partial_args([&](auto &, auto &needle) {arguments[key_res->prelude + needle] = "";});
throw common_chat_msg_partial_exception("Partial literal: " + gbnf_format_literal(form.key_val_sep));
}
auto &key = key_res->prelude;
recovery = false;
// Parse arg_value
if (form.key_val_sep2) {
if (auto tc = builder.try_find_literal(*form.key_val_sep2)) {
if (!all_space(tc->prelude)) {
LOG_DBG("Failed to parse XML-Style tool call: Unexcepted %s between %s and %s\n",
gbnf_format_literal(tc->prelude).c_str(),
gbnf_format_literal(form.key_val_sep).c_str(),
gbnf_format_literal(*form.key_val_sep2).c_str()
);
return return_error(builder, start_pos, false);
}
if (tc->groups[0].end - tc->groups[0].begin != form.key_val_sep2->size()) {
gen_partial_args([&](auto &, auto &needle) {arguments[key] = needle;});
throw common_chat_msg_partial_exception("Partial literal: " + gbnf_format_literal(*form.key_val_sep2));
}
} else {
gen_partial_args([&](auto &, auto &needle) {arguments[key] = needle;});
throw common_chat_msg_partial_exception("Expected " + gbnf_format_literal(*form.key_val_sep2) + " after " + gbnf_format_literal(form.key_val_sep));
}
}
auto val_start = builder.pos();
// Test if arg_val is a partial JSON
std::optional<common_json> value_json = std::nullopt;
if (!form.raw_argval || !*form.raw_argval) {
try { value_json = builder.try_consume_json(); }
catch (const std::runtime_error&) { builder.move_to(val_start); }
// TODO: Delete this when json_partial adds top-level support for null/true/false
if (builder.pos() == val_start) {
const static std::regex number_regex(R"([0-9-][0-9]*(\.\d*)?([eE][+-]?\d*)?)");
builder.consume_spaces();
std::string_view sv = utf8_truncate_safe_view(builder.input());
sv.remove_prefix(builder.pos());
std::string rest = "a";
if (sv.size() < 6) rest = sv;
if (string_starts_with("null", rest) || string_starts_with("true", rest) || string_starts_with("false", rest) || std::regex_match(sv.begin(), sv.end(), number_regex)) {
value_json = {123, {"123", "123"}};
builder.consume_rest();
} else {
builder.move_to(val_start);
}
}
}
// If it is a JSON and followed by </arg_value>, parse as json
// cannot support streaming because it may be a plain text starting with JSON
if (value_json) {
auto json_end = builder.pos();
builder.consume_spaces();
if (builder.pos() == builder.input().size()) {
if (form.raw_argval && !*form.raw_argval && (value_json->json.is_string() || value_json->json.is_object() || value_json->json.is_array())) {
arguments[key] = value_json->json;
auto json_str = arguments.dump();
if (!value_json->healing_marker.json_dump_marker.empty()) {
GGML_ASSERT(std::string::npos != json_str.rfind(value_json->healing_marker.json_dump_marker));
json_str.resize(json_str.rfind(value_json->healing_marker.json_dump_marker));
} else {
GGML_ASSERT(json_str.back() == '}');
json_str.resize(json_str.size() - 1);
}
builder.add_tool_call(function_name, "", json_str);
} else {
gen_partial_args([&](auto &, auto &needle) {arguments[key] = needle;});
}
LOG_DBG("Possible JSON arg_value: %s\n", value_json->json.dump().c_str());
throw common_chat_msg_partial_exception("JSON arg_value detected. Waiting for more tokens for validations.");
}
builder.move_to(json_end);
auto [val_end_size, tc] = try_find_val_end();
if (tc && all_space(tc->prelude) && value_json->healing_marker.marker.empty()) {
if (tc->groups[0].end - tc->groups[0].begin != val_end_size) {
gen_partial_args([&](auto &, auto &needle) {arguments[key] = needle;});
LOG_DBG("Possible terminated JSON arg_value: %s\n", value_json->json.dump().c_str());
throw common_chat_msg_partial_exception("Partial literal: " + gbnf_format_literal(form.val_end) + (form.last_val_end ? gbnf_format_literal(*form.last_val_end) : ""));
} else arguments[key] = value_json->json;
} else builder.move_to(val_start);
}
// If not, parse as plain text
if (val_start == builder.pos()) {
if (auto [val_end_size, value_plain] = try_find_val_end(); value_plain) {
auto &value_str = value_plain->prelude;
if (form.trim_raw_argval) value_str = string_strip(value_str);
if (value_plain->groups[0].end - value_plain->groups[0].begin != val_end_size) {
gen_partial_args([&](auto &, auto &needle) {arguments[key] = value_str + needle;});
throw common_chat_msg_partial_exception(
"Expected " + gbnf_format_literal(form.val_end) +
" after " + gbnf_format_literal(form.key_val_sep) +
(form.key_val_sep2 ? " " + gbnf_format_literal(*form.key_val_sep2) : "")
);
}
arguments[key] = value_str;
} else {
if (form.trim_raw_argval) {
gen_partial_args([&](auto &rest, auto &needle) {arguments[key] = string_strip(rest) + needle;});
} else {
gen_partial_args([&](auto &rest, auto &needle) {arguments[key] = rest + needle;});
}
throw common_chat_msg_partial_exception(
"Expected " + gbnf_format_literal(form.val_end) +
" after " + gbnf_format_literal(form.key_val_sep) +
(form.key_val_sep2 ? " " + gbnf_format_literal(*form.key_val_sep2) : "")
);
}
}
}
// Consume closing tag
if (auto [tool_end_size, tc] = try_find_tool_end(); tc) {
if (!all_space(tc->prelude)) {
LOG_DBG("Failed to parse XML-Style tool call: Expected %s, but found %s\n",
gbnf_format_literal(form.tool_end).c_str(),
gbnf_format_literal(tc->prelude).c_str()
);
return return_error(builder, start_pos, recovery);
}
if (tc->groups[0].end - tc->groups[0].begin == tool_end_size) {
// Add the parsed tool call
if (!builder.add_tool_call(function_name, "", arguments.dump())) {
throw common_chat_msg_partial_exception("Failed to add XML-Style tool call");
}
recovery = false;
continue;
}
}
auto tool_call_arg = arguments.dump();
if (tool_call_arg.size() != 0 && tool_call_arg[tool_call_arg.size() - 1] == '}') {
tool_call_arg.resize(tool_call_arg.size() - 1);
}
builder.add_tool_call(function_name, "", tool_call_arg);
throw common_chat_msg_partial_exception("Expected " + gbnf_format_literal(form.tool_end) + " after " + gbnf_format_literal(form.val_end));
}
if (auto tc = builder.try_find_literal(form.scope_end)) {
if (!all_space(tc->prelude)) {
LOG_DBG("Failed to parse XML-Style tool call: Expected %s, but found %s\n",
gbnf_format_literal(form.scope_end).c_str(),
gbnf_format_literal(tc->prelude).c_str()
);
return return_error(builder, start_pos, recovery);
}
} else {
if (all_space(form.scope_end)) return true;
builder.consume_spaces();
if (builder.pos() == builder.input().size())
throw common_chat_msg_partial_exception("incomplete tool calls");
LOG_DBG("Failed to parse XML-Style tool call: Expected %s, but found %s\n",
gbnf_format_literal(form.scope_end).c_str(),
gbnf_format_literal(builder.consume_rest()).c_str()
);
return return_error(builder, start_pos, recovery);
}
return true;
}
/**
* Parse XML-Style tool call for given xml_tool_call_format. Return false for invalid syntax and get the position untouched.
* May cause std::runtime_error if there is invalid syntax because partial valid tool call is already sent out to client.
* form.scope_start, form.tool_sep and form.scope_end can be empty.
*/
bool common_chat_msg_parser::try_consume_xml_tool_calls(const struct xml_tool_call_format & form) {
auto pos = pos_;
auto tsize = result_.tool_calls.size();
try { return parse_xml_tool_calls(*this, form); }
catch (const xml_toolcall_syntax_exception&) {}
move_to(pos);
result_.tool_calls.resize(tsize);
return false;
}
/**
* Parse content uses reasoning and XML-Style tool call
* TODO: Note that form.allow_toolcall_in_think is not tested yet. If anyone confirms it works, this comment can be removed.
*/
inline void parse_msg_with_xml_tool_calls(common_chat_msg_parser & builder, const struct xml_tool_call_format & form, const std::string & start_think = "<think>", const std::string & end_think = "</think>") {
constexpr auto rstrip = [](std::string &s) {
s.resize(std::distance(s.begin(), std::find_if(s.rbegin(), s.rend(), [](unsigned char ch) { return !std::isspace(ch); }).base()));
};
// Erase substring from l to r, along with additional spaces nearby
constexpr auto erase_spaces = [](auto &str, size_t l, size_t r) {
while (/* l > -1 && */ --l < str.size() && std::isspace(static_cast<unsigned char>(str[l])));
++l;
while (++r < str.size() && std::isspace(static_cast<unsigned char>(str[r])));
if (l < r) str[l] = '\n';
if (l + 1 < r) str[l + 1] = '\n';
if (l != 0) l += 2;
str.erase(l, r - l);
return l;
};
constexpr auto trim_suffix = [](std::string &content, std::initializer_list<std::string_view> list) {
auto best_match = content.size();
for (auto pattern: list) {
if (pattern.size() == 0) continue;
for (auto match_idx = content.size() - std::min(pattern.size(), content.size()); content.size() > match_idx; match_idx++) {
auto match_len = content.size() - match_idx;
if (content.compare(match_idx, match_len, pattern.data(), match_len) == 0 && best_match > match_idx) {
best_match = match_idx;
}
}
}
if (content.size() > best_match) {
content.erase(best_match);
}
};
const auto trim_potential_partial_word = [&start_think, &end_think, &form, trim_suffix](std::string &content) {
return trim_suffix(content, {
start_think, end_think, form.scope_start, form.tool_start, form.tool_sep, form.key_start,
form.key_val_sep, form.key_val_sep2 ? form.key_val_sep2->c_str() : "",
form.val_end, form.last_val_end ? form.last_val_end->c_str() : "",
form.tool_end, form.last_tool_end ? form.last_tool_end->c_str() : "",
form.scope_end
});
};
// Trim leading spaces without affecting keyword matching
static const common_regex spaces_regex("\\s*");
{
auto tc = builder.consume_regex(spaces_regex);
auto spaces = builder.str(tc.groups[0]);
auto s1 = spaces.size();
trim_potential_partial_word(spaces);
auto s2 = spaces.size();
builder.move_to(builder.pos() - (s1 - s2));
}
// Parse content
bool reasoning_unclosed = builder.syntax().thinking_forced_open;
std::string unclosed_reasoning_content("");
for (;;) {
auto tc = try_find_2_literal_splited_by_spaces(builder, form.scope_start, form.tool_start);
std::string content;
std::string tool_call_start;
if (tc) {
content = std::move(tc->prelude);
tool_call_start = builder.str(tc->groups[0]);
LOG_DBG("Matched tool start: %s\n", gbnf_format_literal(tool_call_start).c_str());
} else {
content = builder.consume_rest();
utf8_truncate_safe_resize(content);
}
// Handle unclosed think block
if (reasoning_unclosed) {
if (auto pos = content.find(end_think); pos == std::string::npos && builder.pos() != builder.input().size()) {
unclosed_reasoning_content += content;
if (!(form.allow_toolcall_in_think && tc)) {
unclosed_reasoning_content += tool_call_start;
continue;
}
} else {
reasoning_unclosed = false;
std::string reasoning_content;
if (pos == std::string::npos) {
reasoning_content = std::move(content);
} else {
reasoning_content = content.substr(0, pos);
content.erase(0, pos + end_think.size());
}
if (builder.pos() == builder.input().size() && all_space(content)) {
rstrip(reasoning_content);
trim_potential_partial_word(reasoning_content);
rstrip(reasoning_content);
if (reasoning_content.empty()) {
rstrip(unclosed_reasoning_content);
trim_potential_partial_word(unclosed_reasoning_content);
rstrip(unclosed_reasoning_content);
if (unclosed_reasoning_content.empty()) continue;
}
}
if (builder.syntax().reasoning_format == COMMON_REASONING_FORMAT_NONE || builder.syntax().reasoning_in_content) {
builder.add_content(start_think);
builder.add_content(unclosed_reasoning_content);
builder.add_content(reasoning_content);
if (builder.pos() != builder.input().size() || !all_space(content))
builder.add_content(end_think);
} else {
builder.add_reasoning_content(unclosed_reasoning_content);
builder.add_reasoning_content(reasoning_content);
}
unclosed_reasoning_content.clear();
}
}
// Handle multiple think block
bool toolcall_in_think = false;
for (auto think_start = content.find(start_think); think_start != std::string::npos; think_start = content.find(start_think, think_start)) {
if (auto think_end = content.find(end_think, think_start + start_think.size()); think_end != std::string::npos) {
if (builder.syntax().reasoning_format != COMMON_REASONING_FORMAT_NONE && !builder.syntax().reasoning_in_content) {
auto reasoning_content = content.substr(think_start + start_think.size(), think_end - think_start - start_think.size());
builder.add_reasoning_content(reasoning_content);
think_start = erase_spaces(content, think_start, think_end + end_think.size() - 1);
} else {
think_start = think_end + end_think.size() - 1;
}
} else {
// This <tool_call> start is in thinking block, skip this tool call
// This <tool_call> start is in thinking block
if (form.allow_toolcall_in_think) {
unclosed_reasoning_content = content.substr(think_start + start_think.size());
} else {
unclosed_reasoning_content = content.substr(think_start + start_think.size()) + tool_call_start;
}
reasoning_unclosed = true;
content.resize(think_start);
toolcall_in_think = true;
}
}
if (builder.syntax().reasoning_format != COMMON_REASONING_FORMAT_NONE && !builder.syntax().reasoning_in_content) {
rstrip(content);
// Handle unclosed </think> token from content: delete all </think> token
if (auto pos = content.rfind(end_think); pos != std::string::npos) {
while (pos != std::string::npos) {
pos = erase_spaces(content, pos, pos + end_think.size() - 1);
pos = content.rfind(end_think, pos);
}
}
// Strip if needed
if (content.size() > 0 && std::isspace(static_cast<unsigned char>(content[0]))) {
content = string_strip(content);
}
}
// remove potential partial suffix
if (builder.pos() == builder.input().size()) {
if (unclosed_reasoning_content.empty()) {
rstrip(content);
trim_potential_partial_word(content);
rstrip(content);
} else {
rstrip(unclosed_reasoning_content);
trim_potential_partial_word(unclosed_reasoning_content);
rstrip(unclosed_reasoning_content);
}
}
// consume unclosed_reasoning_content if allow_toolcall_in_think is set
if (form.allow_toolcall_in_think && !unclosed_reasoning_content.empty()) {
if (builder.syntax().reasoning_format != COMMON_REASONING_FORMAT_NONE && !builder.syntax().reasoning_in_content) {
builder.add_reasoning_content(unclosed_reasoning_content);
} else {
if (content.empty()) {
content = start_think + unclosed_reasoning_content;
} else {
content += "\n\n" + start_think;
content += unclosed_reasoning_content;
}
}
unclosed_reasoning_content.clear();
}
// Add content
if (!content.empty()) {
// If there are multiple content blocks
if (builder.syntax().reasoning_format != COMMON_REASONING_FORMAT_NONE && !builder.syntax().reasoning_in_content && builder.result().content.size() != 0) {
builder.add_content("\n\n");
}
builder.add_content(content);
}
// This <tool_call> start is in thinking block and toolcall_in_think not set, skip this tool call
if (toolcall_in_think && !form.allow_toolcall_in_think) {
continue;
}
// There is no tool call and all content is parsed
if (!tc) {
GGML_ASSERT(builder.pos() == builder.input().size());
GGML_ASSERT(unclosed_reasoning_content.empty());
if (!form.allow_toolcall_in_think) GGML_ASSERT(!reasoning_unclosed);
break;
}
builder.move_to(tc->groups[0].begin);
if (builder.try_consume_xml_tool_calls(form)) {
auto end_of_tool = builder.pos();
builder.consume_spaces();
if (builder.pos() != builder.input().size()) {
builder.move_to(end_of_tool);
if (!builder.result().content.empty()) {
builder.add_content("\n\n");
}
}
} else {
static const common_regex next_char_regex(".");
auto c = builder.str(builder.consume_regex(next_char_regex).groups[0]);
rstrip(c);
builder.add_content(c);
}
}
}
/**
* Parse content uses reasoning and XML-Style tool call
*/
void common_chat_msg_parser::consume_reasoning_with_xml_tool_calls(const struct xml_tool_call_format & form, const std::string & start_think, const std::string & end_think) {
parse_msg_with_xml_tool_calls(*this, form, start_think, end_think);
}

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#pragma once
#include "chat.h"
#include <nlohmann/json.hpp>
#include <optional>
#include <string>
#include <vector>
// Sample config:
// MiniMax-M2 (left): <minimax:tool_call>\n<invoke name="tool-name">\n<parameter name="key">value</parameter>\n...</invoke>\n...</minimax:tool_call>
// GLM 4.5 (right): <tool_call>function_name\n<arg_key>key</arg_key>\n<arg_value>value</arg_value>\n</tool_call>
struct xml_tool_call_format {
std::string scope_start; // <minimax:tool_call>\n // \n // can be empty
std::string tool_start; // <invoke name=\" // <tool_call>
std::string tool_sep; // \">\n // \n // can be empty only for parse_xml_tool_calls
std::string key_start; // <parameter name=\" // <arg_key>
std::string key_val_sep; // \"> // </arg_key>\n<arg_value>
std::string val_end; // </parameter>\n // </arg_value>\n
std::string tool_end; // </invoke>\n // </tool_call>\n
std::string scope_end; // </minimax:tool_call> // // can be empty
// Set this if there can be dynamic spaces inside key_val_sep.
// e.g. key_val_sep=</arg_key> key_val_sep2=<arg_value> for GLM4.5
std::optional<std::string> key_val_sep2 = std::nullopt;
// Set true if argval should only be raw string. e.g. Hello "world" hi
// Set false if argval should only be json string. e.g. "Hello \"world\" hi"
// Defaults to std::nullopt, both will be allowed.
std::optional<bool> raw_argval = std::nullopt;
std::optional<std::string> last_val_end = std::nullopt;
std::optional<std::string> last_tool_end = std::nullopt;
bool trim_raw_argval = false;
bool allow_toolcall_in_think = false;
};
// make a GBNF that accept any strings except those containing any of the forbidden strings.
std::string make_gbnf_excluding(std::vector<std::string> forbids);
/**
* Build grammar for xml-style tool call
* form.scope_start and form.scope_end can be empty.
* Requires data.format for model-specific hacks.
*/
void build_grammar_xml_tool_call(common_chat_params & data, const nlohmann::ordered_json & tools, const struct xml_tool_call_format & form);

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#pragma once
#include "chat.h"
#include "chat-parser-xml-toolcall.h"
#include "json-partial.h"
#include "regex-partial.h"
#include <nlohmann/json_fwd.hpp>
#include <optional>
#include <string>
#include <vector>
class common_chat_msg_partial_exception : public std::runtime_error {
public:
common_chat_msg_partial_exception(const std::string & message) : std::runtime_error(message) {}
};
class common_chat_msg_parser {
std::string input_;
bool is_partial_;
common_chat_parser_params syntax_; // TODO: rename to params
std::string healing_marker_;
size_t pos_ = 0;
common_chat_msg result_;
public:
common_chat_msg_parser(const std::string & input, bool is_partial, const common_chat_parser_params & syntax);
const std::string & input() const { return input_; }
size_t pos() const { return pos_; }
const std::string & healing_marker() const { return healing_marker_; }
const bool & is_partial() const { return is_partial_; }
const common_chat_msg & result() const { return result_; }
const common_chat_parser_params & syntax() const { return syntax_; }
void move_to(size_t pos) {
if (pos > input_.size()) {
throw std::runtime_error("Invalid position!");
}
pos_ = pos;
}
void move_back(size_t n) {
if (pos_ < n) {
throw std::runtime_error("Can't move back that far!");
}
pos_ -= n;
}
// Get the substring of the input at the given range
std::string str(const common_string_range & rng) const;
// Appends to the result.content field
void add_content(const std::string & content);
// Appends to the result.reasoning_content field
void add_reasoning_content(const std::string & reasoning_content);
// Adds a tool call to the result. If the tool call is too incomplete (e.g. name empty), it won't add anything.
bool add_tool_call(const std::string & name, const std::string & id, const std::string & arguments);
// Adds a tool call using the "name", "id" and "arguments" fields of the json object
bool add_tool_call(const nlohmann::ordered_json & tool_call);
// Adds an array of tool calls using their "name", "id" and "arguments" fields.
bool add_tool_calls(const nlohmann::ordered_json & arr);
// Adds a tool call using the short form: { "tool_name": { "arg1": val, "arg2": val } }
bool add_tool_call_short_form(const nlohmann::ordered_json & tool_call);
void finish();
bool consume_spaces();
void consume_literal(const std::string & literal);
bool try_parse_reasoning(const std::string & start_think, const std::string & end_think);
std::string consume_rest();
struct find_regex_result {
std::string prelude;
std::vector<common_string_range> groups;
};
std::optional<find_regex_result> try_find_regex(const common_regex & regex, size_t from = std::string::npos, bool add_prelude_to_content = true);
bool try_consume_literal(const std::string & literal);
std::optional<find_regex_result> try_find_literal(const std::string & literal);
find_regex_result consume_regex(const common_regex & regex);
std::optional<find_regex_result> try_consume_regex(const common_regex & regex);
std::optional<common_json> try_consume_json();
common_json consume_json();
struct consume_json_result {
nlohmann::ordered_json value;
bool is_partial;
};
/*
Consume (possibly partial) json and converts specific subtrees to (possibly truncated) JSON strings.
By default, object keys can't be truncated, nor can string values (their corresponding key is removed,
e.g. `{"foo": "bar", "baz": "b` -> `{"foo": "bar"}`
But one can allow subpaths to be kept truncated, and possibly json-dumped to truncated json strings
- with `content_paths={{"foo"}}` -> `{"foo": "b` -> {"foo": "b"}`
- with `args_paths={{"foo"}}` -> `{"foo": {"b` -> `{"foo": "{b"}`
*/
consume_json_result consume_json_with_dumped_args(
const std::vector<std::vector<std::string>> & args_paths = {},
const std::vector<std::vector<std::string>> & content_paths = {}
);
std::optional<consume_json_result> try_consume_json_with_dumped_args(
const std::vector<std::vector<std::string>> & args_paths = {},
const std::vector<std::vector<std::string>> & content_paths = {}
);
/**
* Parse XML-Style tool call for given xml_tool_call_format. Return false for invalid syntax and get the position untouched.
* form.scope_start, form.tool_sep and form.scope_end can be empty.
*/
bool try_consume_xml_tool_calls(const struct xml_tool_call_format & form);
// Parse content uses reasoning and XML-Style tool call
void consume_reasoning_with_xml_tool_calls(const struct xml_tool_call_format & form, const std::string & start_think = "<think>", const std::string & end_think = "</think>");
void clear_tools();
};

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#include "chat-peg-parser.h"
#include <nlohmann/json.hpp>
using json = nlohmann::json;
static std::string_view trim_trailing_space(std::string_view sv, int max = -1) {
int count = 0;
while (!sv.empty() && std::isspace(static_cast<unsigned char>(sv.back()))) {
if (max != -1 && count <= max) {
break;
}
sv.remove_suffix(1);
count++;
}
return sv;
}
void common_chat_peg_mapper::from_ast(const common_peg_ast_arena & arena, const common_peg_parse_result & result) {
arena.visit(result, [this](const common_peg_ast_node & node) {
map(node);
});
}
void common_chat_peg_mapper::map(const common_peg_ast_node & node) {
bool is_reasoning = node.tag == common_chat_peg_builder::REASONING;
bool is_content = node.tag == common_chat_peg_builder::CONTENT;
if (is_reasoning) {
result.reasoning_content = std::string(trim_trailing_space(node.text));
}
if (is_content) {
result.content = std::string(trim_trailing_space(node.text));
}
}
void common_chat_peg_native_mapper::map(const common_peg_ast_node & node) {
common_chat_peg_mapper::map(node);
bool is_tool_open = node.tag == common_chat_peg_native_builder::TOOL_OPEN;
bool is_tool_name = node.tag == common_chat_peg_native_builder::TOOL_NAME;
bool is_tool_id = node.tag == common_chat_peg_native_builder::TOOL_ID;
bool is_tool_args = node.tag == common_chat_peg_native_builder::TOOL_ARGS;
if (is_tool_open) {
result.tool_calls.emplace_back();
current_tool = &result.tool_calls.back();
}
if (is_tool_id && current_tool) {
current_tool->id = std::string(trim_trailing_space(node.text));
}
if (is_tool_name && current_tool) {
current_tool->name = std::string(trim_trailing_space(node.text));
}
if (is_tool_args && current_tool) {
current_tool->arguments = std::string(trim_trailing_space(node.text));
}
}
void common_chat_peg_constructed_mapper::map(const common_peg_ast_node & node) {
common_chat_peg_mapper::map(node);
bool is_tool_open = node.tag == common_chat_peg_constructed_builder::TOOL_OPEN;
bool is_tool_name = node.tag == common_chat_peg_constructed_builder::TOOL_NAME;
bool is_tool_close = node.tag == common_chat_peg_constructed_builder::TOOL_CLOSE;
bool is_arg_open = node.tag == common_chat_peg_constructed_builder::TOOL_ARG_OPEN;
bool is_arg_close = node.tag == common_chat_peg_constructed_builder::TOOL_ARG_CLOSE;
bool is_arg_name = node.tag == common_chat_peg_constructed_builder::TOOL_ARG_NAME;
bool is_arg_string = node.tag == common_chat_peg_constructed_builder::TOOL_ARG_STRING_VALUE;
bool is_arg_json = node.tag == common_chat_peg_constructed_builder::TOOL_ARG_JSON_VALUE;
if (is_tool_open) {
result.tool_calls.emplace_back();
current_tool = &result.tool_calls.back();
arg_count = 0;
}
if (is_tool_name) {
current_tool->name = std::string(node.text);
current_tool->arguments = "{";
}
if (is_arg_open) {
needs_closing_quote = false;
}
if (is_arg_name && current_tool) {
if (arg_count > 0) {
current_tool->arguments += ",";
}
current_tool->arguments += json(trim_trailing_space(node.text)).dump() + ":";
++arg_count;
}
if (is_arg_string && current_tool) {
// Serialize to JSON, but exclude the end quote
std::string dumped = json(trim_trailing_space(node.text)).dump();
current_tool->arguments += dumped.substr(0, dumped.size() - 1);
needs_closing_quote = true;
}
if (is_arg_close && current_tool) {
if (needs_closing_quote) {
current_tool->arguments += "\"";
needs_closing_quote = false;
}
}
if (is_arg_json && current_tool) {
current_tool->arguments += std::string(trim_trailing_space(node.text));
}
if (is_tool_close && current_tool) {
if (needs_closing_quote) {
current_tool->arguments += "\"";
needs_closing_quote = false;
}
current_tool->arguments += "}";
}
}

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#pragma once
#include "chat.h"
#include "peg-parser.h"
class common_chat_peg_builder : public common_peg_parser_builder {
public:
static constexpr const char * REASONING_BLOCK = "reasoning-block";
static constexpr const char * REASONING = "reasoning";
static constexpr const char * CONTENT = "content";
common_peg_parser reasoning_block(const common_peg_parser & p) { return tag(REASONING_BLOCK, p); }
common_peg_parser reasoning(const common_peg_parser & p) { return tag(REASONING, p); }
common_peg_parser content(const common_peg_parser & p) { return tag(CONTENT, p); }
};
inline common_peg_arena build_chat_peg_parser(const std::function<common_peg_parser(common_chat_peg_builder & builder)> & fn) {
common_chat_peg_builder builder;
builder.set_root(fn(builder));
return builder.build();
}
class common_chat_peg_mapper {
public:
common_chat_msg & result;
common_chat_peg_mapper(common_chat_msg & msg) : result(msg) {}
virtual void from_ast(const common_peg_ast_arena & arena, const common_peg_parse_result & result);
virtual void map(const common_peg_ast_node & node);
};
class common_chat_peg_native_builder : public common_chat_peg_builder {
public:
static constexpr const char * TOOL = "tool";
static constexpr const char * TOOL_OPEN = "tool-open";
static constexpr const char * TOOL_CLOSE = "tool-close";
static constexpr const char * TOOL_ID = "tool-id";
static constexpr const char * TOOL_NAME = "tool-name";
static constexpr const char * TOOL_ARGS = "tool-args";
common_peg_parser tool(const common_peg_parser & p) { return tag(TOOL, p); }
common_peg_parser tool_open(const common_peg_parser & p) { return atomic(tag(TOOL_OPEN, p)); }
common_peg_parser tool_close(const common_peg_parser & p) { return atomic(tag(TOOL_CLOSE, p)); }
common_peg_parser tool_id(const common_peg_parser & p) { return atomic(tag(TOOL_ID, p)); }
common_peg_parser tool_name(const common_peg_parser & p) { return atomic(tag(TOOL_NAME, p)); }
common_peg_parser tool_args(const common_peg_parser & p) { return tag(TOOL_ARGS, p); }
};
class common_chat_peg_native_mapper : public common_chat_peg_mapper {
common_chat_tool_call * current_tool;
public:
common_chat_peg_native_mapper(common_chat_msg & msg) : common_chat_peg_mapper(msg) {}
void map(const common_peg_ast_node & node) override;
};
inline common_peg_arena build_chat_peg_native_parser(const std::function<common_peg_parser(common_chat_peg_native_builder & builder)> & fn) {
common_chat_peg_native_builder builder;
builder.set_root(fn(builder));
return builder.build();
}
class common_chat_peg_constructed_builder : public common_chat_peg_builder {
public:
static constexpr const char * TOOL = "tool";
static constexpr const char * TOOL_OPEN = "tool-open";
static constexpr const char * TOOL_CLOSE = "tool-close";
static constexpr const char * TOOL_NAME = "tool-name";
static constexpr const char * TOOL_ARG = "tool-arg";
static constexpr const char * TOOL_ARG_OPEN = "tool-arg-open";
static constexpr const char * TOOL_ARG_CLOSE = "tool-arg-close";
static constexpr const char * TOOL_ARG_NAME = "tool-arg-name";
static constexpr const char * TOOL_ARG_STRING_VALUE = "tool-arg-string-value";
static constexpr const char * TOOL_ARG_JSON_VALUE = "tool-arg-json-value";
common_peg_parser tool(const common_peg_parser & p) { return tag(TOOL, p); }
common_peg_parser tool_open(const common_peg_parser & p) { return atomic(tag(TOOL_OPEN, p)); }
common_peg_parser tool_close(const common_peg_parser & p) { return atomic(tag(TOOL_CLOSE, p)); }
common_peg_parser tool_name(const common_peg_parser & p) { return atomic(tag(TOOL_NAME, p)); }
common_peg_parser tool_arg(const common_peg_parser & p) { return tag(TOOL_ARG, p); }
common_peg_parser tool_arg_open(const common_peg_parser & p) { return atomic(tag(TOOL_ARG_OPEN, p)); }
common_peg_parser tool_arg_close(const common_peg_parser & p) { return atomic(tag(TOOL_ARG_CLOSE, p)); }
common_peg_parser tool_arg_name(const common_peg_parser & p) { return atomic(tag(TOOL_ARG_NAME, p)); }
common_peg_parser tool_arg_string_value(const common_peg_parser & p) { return tag(TOOL_ARG_STRING_VALUE, p); }
common_peg_parser tool_arg_json_value(const common_peg_parser & p) { return tag(TOOL_ARG_JSON_VALUE, p); }
};
class common_chat_peg_constructed_mapper : public common_chat_peg_mapper {
common_chat_tool_call * current_tool;
int arg_count = 0;
bool needs_closing_quote = false;
public:
common_chat_peg_constructed_mapper(common_chat_msg & msg) : common_chat_peg_mapper(msg) {}
void map(const common_peg_ast_node & node) override;
};
inline common_peg_arena build_chat_peg_constructed_parser(const std::function<common_peg_parser(common_chat_peg_constructed_builder & builder)> & fn) {
common_chat_peg_constructed_builder builder;
builder.set_root(fn(builder));
return builder.build();
}

File diff suppressed because it is too large Load Diff

View File

@ -3,14 +3,8 @@
#pragma once
#include "common.h"
#include "peg-parser.h"
#include <functional>
#include <chrono>
#include <string>
#include <vector>
#include <map>
#include <nlohmann/json_fwd.hpp>
struct common_chat_templates;
@ -18,79 +12,21 @@ struct common_chat_tool_call {
std::string name;
std::string arguments;
std::string id;
bool operator==(const common_chat_tool_call & other) const {
return name == other.name && arguments == other.arguments && id == other.id;
}
};
struct common_chat_msg_content_part {
std::string type;
std::string text;
// TODO @ngxson : no known chat templates support reasoning_content in content parts yet
// this can be useful for models with interleaved thinking (like Kimi-K2)
// if you see any templates explicitly support this, please ping me
// std::string reasoning_content;
bool operator==(const common_chat_msg_content_part & other) const {
return type == other.type && text == other.text;
}
};
struct common_chat_msg {
std::string role;
std::string content;
std::vector<common_chat_msg_content_part> content_parts;
std::vector<common_chat_tool_call> tool_calls;
std::vector<common_chat_msg_content_part> content_parts = {};
std::vector<common_chat_tool_call> tool_calls = {};
std::string reasoning_content;
std::string tool_name;
std::string tool_call_id;
nlohmann::ordered_json to_json_oaicompat(bool concat_typed_text = false) const;
bool empty() const {
return content.empty() && content_parts.empty() && tool_calls.empty() && reasoning_content.empty() && tool_name.empty() && tool_call_id.empty();
}
void set_tool_call_ids(std::vector<std::string> & ids_cache, const std::function<std::string()> & gen_tool_call_id) {
for (auto i = 0u; i < tool_calls.size(); i++) {
if (ids_cache.size() <= i) {
auto id = tool_calls[i].id;
if (id.empty()) {
id = gen_tool_call_id();
}
ids_cache.push_back(id);
}
tool_calls[i].id = ids_cache[i];
}
}
bool operator==(const common_chat_msg & other) const {
return role == other.role
&& content == other.content
&& content_parts == other.content_parts
&& tool_calls == other.tool_calls
&& reasoning_content == other.reasoning_content
&& tool_name == other.tool_name
&& tool_call_id == other.tool_call_id;
}
bool operator!=(const common_chat_msg & other) const {
return !(*this == other);
}
};
struct common_chat_msg_diff {
std::string reasoning_content_delta;
std::string content_delta;
size_t tool_call_index = std::string::npos;
common_chat_tool_call tool_call_delta;
static std::vector<common_chat_msg_diff> compute_diffs(const common_chat_msg & msg_prv, const common_chat_msg & msg_new);
bool operator==(const common_chat_msg_diff & other) const {
return content_delta == other.content_delta
&& tool_call_index == other.tool_call_index
&& tool_call_delta == other.tool_call_delta;
}
};
struct common_chat_tool {
@ -109,35 +45,17 @@ enum common_chat_format {
COMMON_CHAT_FORMAT_CONTENT_ONLY,
COMMON_CHAT_FORMAT_GENERIC,
COMMON_CHAT_FORMAT_MISTRAL_NEMO,
COMMON_CHAT_FORMAT_MAGISTRAL,
COMMON_CHAT_FORMAT_LLAMA_3_X,
COMMON_CHAT_FORMAT_LLAMA_3_X_WITH_BUILTIN_TOOLS,
COMMON_CHAT_FORMAT_DEEPSEEK_R1,
COMMON_CHAT_FORMAT_DEEPSEEK_R1_EXTRACT_REASONING,
COMMON_CHAT_FORMAT_FIREFUNCTION_V2,
COMMON_CHAT_FORMAT_FUNCTIONARY_V3_2,
COMMON_CHAT_FORMAT_FUNCTIONARY_V3_1_LLAMA_3_1,
COMMON_CHAT_FORMAT_DEEPSEEK_V3_1,
COMMON_CHAT_FORMAT_HERMES_2_PRO,
COMMON_CHAT_FORMAT_HERMES_2_PRO_EXTRACT_REASONING,
COMMON_CHAT_FORMAT_COMMAND_R7B,
COMMON_CHAT_FORMAT_GRANITE,
COMMON_CHAT_FORMAT_GPT_OSS,
COMMON_CHAT_FORMAT_SEED_OSS,
COMMON_CHAT_FORMAT_NEMOTRON_V2,
COMMON_CHAT_FORMAT_APERTUS,
COMMON_CHAT_FORMAT_LFM2_WITH_JSON_TOOLS,
COMMON_CHAT_FORMAT_GLM_4_5,
COMMON_CHAT_FORMAT_MINIMAX_M2,
COMMON_CHAT_FORMAT_KIMI_K2,
COMMON_CHAT_FORMAT_QWEN3_CODER_XML,
COMMON_CHAT_FORMAT_APRIEL_1_5,
COMMON_CHAT_FORMAT_XIAOMI_MIMO,
COMMON_CHAT_FORMAT_SOLAR_OPEN,
COMMON_CHAT_FORMAT_EXAONE_MOE,
// These are intended to be parsed by the PEG parser
COMMON_CHAT_FORMAT_PEG_SIMPLE,
COMMON_CHAT_FORMAT_PEG_NATIVE,
COMMON_CHAT_FORMAT_PEG_CONSTRUCTED,
COMMON_CHAT_FORMAT_COMMAND_R7B_EXTRACT_REASONING,
COMMON_CHAT_FORMAT_COUNT, // Not a format, just the # formats
};
@ -152,12 +70,7 @@ struct common_chat_templates_inputs {
std::vector<common_chat_tool> tools;
common_chat_tool_choice tool_choice = COMMON_CHAT_TOOL_CHOICE_AUTO;
bool parallel_tool_calls = false;
common_reasoning_format reasoning_format = COMMON_REASONING_FORMAT_NONE; // TODO: refactor this to "bool enable_thinking"
bool enable_thinking = true;
std::chrono::system_clock::time_point now = std::chrono::system_clock::now();
std::map<std::string, std::string> chat_template_kwargs;
bool add_bos = false;
bool add_eos = false;
bool extract_reasoning = true;
};
struct common_chat_params {
@ -165,28 +78,9 @@ struct common_chat_params {
std::string prompt;
std::string grammar;
bool grammar_lazy = false;
bool thinking_forced_open = false;
std::vector<common_grammar_trigger> grammar_triggers;
std::vector<std::string> preserved_tokens;
std::vector<std::string> additional_stops;
std::string parser;
};
// per-message parsing syntax
// should be derived from common_chat_params
struct common_chat_parser_params {
common_chat_format format = COMMON_CHAT_FORMAT_CONTENT_ONLY;
common_reasoning_format reasoning_format = COMMON_REASONING_FORMAT_NONE; // TODO: refactor this to "bool parse_reasoning"
// Whether reasoning_content should be inlined in the content (e.g. for reasoning_format=deepseek in stream mode)
bool reasoning_in_content = false;
bool thinking_forced_open = false;
bool parse_tool_calls = true;
common_peg_arena parser = {};
common_chat_parser_params() = default;
common_chat_parser_params(const common_chat_params & chat_params) {
format = chat_params.format;
thinking_forced_open = chat_params.thinking_forced_open;
}
};
// Check if the template supplied via "--chat-template" is supported or not. Returns true if it's valid
@ -205,7 +99,7 @@ common_chat_templates_ptr common_chat_templates_init(
const std::string & eos_token_override = "");
bool common_chat_templates_was_explicit(const struct common_chat_templates * tmpls);
std::string common_chat_templates_source(const struct common_chat_templates * tmpls, const std::string & variant = "");
const char * common_chat_templates_source(const struct common_chat_templates * tmpls, const char * variant = nullptr);
struct common_chat_params common_chat_templates_apply(
@ -223,29 +117,19 @@ std::string common_chat_format_single(
// Returns an example of formatted chat
std::string common_chat_format_example(
const struct common_chat_templates * tmpls,
bool use_jinja,
const std::map<std::string, std::string> & chat_template_kwargs);
bool use_jinja);
const char* common_chat_format_name(common_chat_format format);
common_chat_msg common_chat_parse(const std::string & input, bool is_partial, const common_chat_parser_params & syntax);
common_chat_msg common_chat_peg_parse(const common_peg_arena & parser, const std::string & input, bool is_partial, const common_chat_parser_params & syntax);
// used by arg and server
const char * common_reasoning_format_name(common_reasoning_format format);
common_reasoning_format common_reasoning_format_from_name(const std::string & format);
std::string common_chat_format_name(common_chat_format format);
common_chat_msg common_chat_parse( const std::string & input, common_chat_format format);
common_chat_tool_choice common_chat_tool_choice_parse_oaicompat(const std::string & tool_choice);
bool common_chat_templates_support_enable_thinking(const common_chat_templates * chat_templates);
// Parses a JSON array of messages in OpenAI's chat completion API format.
std::vector<common_chat_msg> common_chat_msgs_parse_oaicompat(const nlohmann::ordered_json & messages);
nlohmann::ordered_json common_chat_msgs_to_json_oaicompat(const std::vector<common_chat_msg> & msgs, bool concat_typed_text = false);
// T can be std::string containing JSON or nlohmann::ordered_json
template <class T> std::vector<common_chat_msg> common_chat_msgs_parse_oaicompat(const T & messages);
template <class T> T common_chat_msgs_to_json_oaicompat(const std::vector<common_chat_msg> & msgs, bool concat_typed_text = false);
std::vector<common_chat_tool> common_chat_tools_parse_oaicompat(const nlohmann::ordered_json & tools);
nlohmann::ordered_json common_chat_tools_to_json_oaicompat(const std::vector<common_chat_tool> & tools);
nlohmann::ordered_json common_chat_msg_diff_to_json_oaicompat(const common_chat_msg_diff & diff);
// get template caps, useful for reporting to server /props endpoint
std::map<std::string, bool> common_chat_templates_get_caps(const common_chat_templates * chat_templates);
// Parses a JSON array of tools in OpenAI's chat completion tool call API format.
// T can be std::string containing JSON or nlohmann::ordered_json
template <class T> std::vector<common_chat_tool> common_chat_tools_parse_oaicompat(const T & tools);
template <class T> T common_chat_tools_to_json_oaicompat(const std::vector<common_chat_tool> & tools);

View File

@ -0,0 +1,24 @@
include(${CMAKE_CURRENT_SOURCE_DIR}/cmake/build-info.cmake)
set(TEMPLATE_FILE "${CMAKE_CURRENT_SOURCE_DIR}/common/build-info.cpp.in")
set(OUTPUT_FILE "${CMAKE_CURRENT_SOURCE_DIR}/common/build-info.cpp")
# Only write the build info if it changed
if(EXISTS ${OUTPUT_FILE})
file(READ ${OUTPUT_FILE} CONTENTS)
string(REGEX MATCH "LLAMA_COMMIT = \"([^\"]*)\";" _ ${CONTENTS})
set(OLD_COMMIT ${CMAKE_MATCH_1})
string(REGEX MATCH "LLAMA_COMPILER = \"([^\"]*)\";" _ ${CONTENTS})
set(OLD_COMPILER ${CMAKE_MATCH_1})
string(REGEX MATCH "LLAMA_BUILD_TARGET = \"([^\"]*)\";" _ ${CONTENTS})
set(OLD_TARGET ${CMAKE_MATCH_1})
if (
NOT OLD_COMMIT STREQUAL BUILD_COMMIT OR
NOT OLD_COMPILER STREQUAL BUILD_COMPILER OR
NOT OLD_TARGET STREQUAL BUILD_TARGET
)
configure_file(${TEMPLATE_FILE} ${OUTPUT_FILE})
endif()
else()
configure_file(${TEMPLATE_FILE} ${OUTPUT_FILE})
endif()

View File

@ -8,14 +8,12 @@
#include "common.h"
#include "log.h"
#include "llama.h"
#include "sampling.h"
#include <algorithm>
#include <cinttypes>
#include <climits>
#include <cmath>
#include <codecvt>
#include <chrono>
#include <cstdarg>
#include <cstring>
#include <ctime>
@ -27,6 +25,7 @@
#include <sstream>
#include <string>
#include <thread>
#include <unordered_map>
#include <unordered_set>
#include <vector>
@ -42,7 +41,6 @@
#endif
#include <locale>
#include <windows.h>
#include <string.h>
#include <fcntl.h>
#include <io.h>
#else
@ -51,23 +49,10 @@
#include <unistd.h>
#endif
#if defined(__linux__)
#include <sys/types.h>
#include <pwd.h>
#endif
#if defined(_MSC_VER)
#pragma warning(disable: 4244 4267) // possible loss of data
#endif
common_time_meas::common_time_meas(int64_t & t_acc, bool disable) : t_start_us(disable ? -1 : ggml_time_us()), t_acc(t_acc) {}
common_time_meas::~common_time_meas() {
if (t_start_us >= 0) {
t_acc += ggml_time_us() - t_start_us;
}
}
//
// CPU utils
//
@ -218,7 +203,6 @@ bool set_process_priority(enum ggml_sched_priority prio) {
DWORD p = NORMAL_PRIORITY_CLASS;
switch (prio) {
case GGML_SCHED_PRIO_LOW: p = BELOW_NORMAL_PRIORITY_CLASS; break;
case GGML_SCHED_PRIO_NORMAL: p = NORMAL_PRIORITY_CLASS; break;
case GGML_SCHED_PRIO_MEDIUM: p = ABOVE_NORMAL_PRIORITY_CLASS; break;
case GGML_SCHED_PRIO_HIGH: p = HIGH_PRIORITY_CLASS; break;
@ -244,14 +228,13 @@ bool set_process_priority(enum ggml_sched_priority prio) {
int p = 0;
switch (prio) {
case GGML_SCHED_PRIO_LOW: p = 5; break;
case GGML_SCHED_PRIO_NORMAL: p = 0; break;
case GGML_SCHED_PRIO_MEDIUM: p = -5; break;
case GGML_SCHED_PRIO_HIGH: p = -10; break;
case GGML_SCHED_PRIO_REALTIME: p = -20; break;
}
if (setpriority(PRIO_PROCESS, 0, p) != 0) {
if (!setpriority(PRIO_PROCESS, 0, p)) {
LOG_WRN("failed to set process priority %d : %s (%d)\n", prio, strerror(errno), errno);
return false;
}
@ -363,7 +346,11 @@ bool parse_cpu_mask(const std::string & mask, bool (&boolmask)[GGML_MAX_N_THREAD
}
void common_init() {
llama_log_set(common_log_default_callback, NULL);
llama_log_set([](ggml_log_level level, const char * text, void * /*user_data*/) {
if (LOG_DEFAULT_LLAMA <= common_log_verbosity_thold) {
common_log_add(common_log_main(), level, "%s", text);
}
}, NULL);
#ifdef NDEBUG
const char * build_type = "";
@ -456,37 +443,9 @@ void string_replace_all(std::string & s, const std::string & search, const std::
s = std::move(builder);
}
bool string_ends_with(const std::string_view & str, const std::string_view & suffix) {
return str.size() >= suffix.size() && str.compare(str.size()-suffix.size(), suffix.size(), suffix) == 0;
}
bool string_remove_suffix(std::string & str, const std::string_view & suffix) {
bool has_suffix = string_ends_with(str, suffix);
if (has_suffix) {
str = str.substr(0, str.size() - suffix.size());
}
return has_suffix;
}
size_t string_find_partial_stop(const std::string_view & str, const std::string_view & stop) {
if (!str.empty() && !stop.empty()) {
const char text_last_char = str.back();
for (int64_t char_index = stop.size() - 1; char_index >= 0; char_index--) {
if (stop[char_index] == text_last_char) {
const auto current_partial = stop.substr(0, char_index + 1);
if (string_ends_with(str, current_partial)) {
return str.size() - char_index - 1;
}
}
}
}
return std::string::npos;
}
std::string regex_escape(const std::string & s) {
static const std::regex special_chars("[.^$|()*+?\\[\\]{}\\\\]");
return std::regex_replace(s, special_chars, "\\$&");
return std::regex_replace(s, special_chars, "\\$0");
}
std::string string_join(const std::vector<std::string> & values, const std::string & separator) {
@ -568,6 +527,13 @@ std::string string_from(const struct llama_context * ctx, const std::vector<llam
auto detokenized = common_token_to_piece(ctx, token);
detokenized.erase(
std::remove_if(
detokenized.begin(),
detokenized.end(),
[](const unsigned char c) { return !std::isprint(c); }),
detokenized.end());
buf << "'" << detokenized << "'"
<< ":" << std::to_string(token);
}
@ -592,6 +558,13 @@ std::string string_from(const struct llama_context * ctx, const struct llama_bat
auto detokenized = common_token_to_piece(ctx, batch.token[i]);
detokenized.erase(
std::remove_if(
detokenized.begin(),
detokenized.end(),
[](const unsigned char c) { return !std::isprint(c); }),
detokenized.end());
buf << "\n" << std::to_string(i)
<< ", token '" << detokenized << "'"
<< ", pos " << std::to_string(batch.pos[i])
@ -694,7 +667,7 @@ bool string_parse_kv_override(const char * data, std::vector<llama_model_kv_over
// Validate if a filename is safe to use
// To validate a full path, split the path by the OS-specific path separator, and validate each part with this function
bool fs_validate_filename(const std::string & filename, bool allow_subdirs) {
bool fs_validate_filename(const std::string & filename) {
if (!filename.length()) {
// Empty filename invalid
return false;
@ -712,17 +685,11 @@ bool fs_validate_filename(const std::string & filename, bool allow_subdirs) {
// disable C++17 deprecation warning for std::codecvt_utf8
# pragma clang diagnostic push
# pragma clang diagnostic ignored "-Wdeprecated-declarations"
#elif defined(__GNUC__)
# pragma GCC diagnostic push
# pragma GCC diagnostic ignored "-Wdeprecated-declarations"
#endif
std::wstring_convert<std::codecvt_utf8<char32_t>, char32_t> converter;
#if defined(__clang__)
# pragma clang diagnostic pop
#elif defined(__GNUC__)
# pragma GCC diagnostic pop
#endif
filename_utf32 = converter.from_bytes(filename);
@ -754,14 +721,10 @@ bool fs_validate_filename(const std::string & filename, bool allow_subdirs) {
|| (c >= 0xD800 && c <= 0xDFFF) // UTF-16 surrogate pairs
|| c == 0xFFFD // Replacement Character (UTF-8)
|| c == 0xFEFF // Byte Order Mark (BOM)
|| c == ':' || c == '*' // Illegal characters
|| c == '/' || c == '\\' || c == ':' || c == '*' // Illegal characters
|| c == '?' || c == '"' || c == '<' || c == '>' || c == '|') {
return false;
}
if (!allow_subdirs && (c == '/' || c == '\\')) {
// Subdirectories not allowed, reject path separators
return false;
}
}
// Reject any leading or trailing ' ', or any trailing '.', these are stripped on Windows and will cause a different filename
@ -783,32 +746,11 @@ bool fs_validate_filename(const std::string & filename, bool allow_subdirs) {
return true;
}
#include <iostream>
#ifdef _WIN32
static std::wstring utf8_to_wstring(const std::string & str) {
if (str.empty()) {
return std::wstring();
}
int size = MultiByteToWideChar(CP_UTF8, 0, str.c_str(), (int)str.size(), NULL, 0);
if (size <= 0) {
return std::wstring();
}
std::wstring wstr(size, 0);
MultiByteToWideChar(CP_UTF8, 0, str.c_str(), (int)str.size(), &wstr[0], size);
return wstr;
}
#endif
// returns true if successful, false otherwise
bool fs_create_directory_with_parents(const std::string & path) {
#ifdef _WIN32
std::wstring wpath = utf8_to_wstring(path);
std::wstring_convert<std::codecvt_utf8<wchar_t>> converter;
std::wstring wpath = converter.from_bytes(path);
// if the path already exists, check whether it's a directory
const DWORD attributes = GetFileAttributesW(wpath.c_str());
@ -821,16 +763,9 @@ bool fs_create_directory_with_parents(const std::string & path) {
// process path from front to back, procedurally creating directories
while ((pos_slash = path.find('\\', pos_slash)) != std::string::npos) {
const std::wstring subpath = wpath.substr(0, pos_slash);
const wchar_t * test = subpath.c_str();
pos_slash += 1;
// skip the drive letter, in some systems it can return an access denied error
if (subpath.length() == 2 && subpath[1] == ':') {
continue;
}
const bool success = CreateDirectoryW(subpath.c_str(), NULL);
const bool success = CreateDirectoryW(test, NULL);
if (!success) {
const DWORD error = GetLastError();
@ -844,6 +779,8 @@ bool fs_create_directory_with_parents(const std::string & path) {
return false;
}
}
pos_slash += 1;
}
return true;
@ -881,11 +818,6 @@ bool fs_create_directory_with_parents(const std::string & path) {
#endif // _WIN32
}
bool fs_is_directory(const std::string & path) {
std::filesystem::path dir(path);
return std::filesystem::exists(dir) && std::filesystem::is_directory(dir);
}
std::string fs_get_cache_directory() {
std::string cache_directory = "";
auto ensure_trailing_slash = [](std::string p) {
@ -898,30 +830,16 @@ std::string fs_get_cache_directory() {
if (getenv("LLAMA_CACHE")) {
cache_directory = std::getenv("LLAMA_CACHE");
} else {
#if defined(__linux__) || defined(__FreeBSD__) || defined(_AIX) || defined(__OpenBSD__)
#if defined(__linux__) || defined(__FreeBSD__) || defined(_AIX)
if (std::getenv("XDG_CACHE_HOME")) {
cache_directory = std::getenv("XDG_CACHE_HOME");
} else if (std::getenv("HOME")) {
cache_directory = std::getenv("HOME") + std::string("/.cache/");
} else {
#if defined(__linux__)
/* no $HOME is defined, fallback to getpwuid */
struct passwd *pw = getpwuid(getuid());
if ((!pw) || (!pw->pw_dir)) {
throw std::runtime_error("Failed to find $HOME directory");
}
cache_directory = std::string(pw->pw_dir) + std::string("/.cache/");
#else /* defined(__linux__) */
throw std::runtime_error("Failed to find $HOME directory");
#endif /* defined(__linux__) */
cache_directory = std::getenv("HOME") + std::string("/.cache/");
}
#elif defined(__APPLE__)
cache_directory = std::getenv("HOME") + std::string("/Library/Caches/");
#elif defined(_WIN32)
cache_directory = std::getenv("LOCALAPPDATA");
#elif defined(__EMSCRIPTEN__)
GGML_ABORT("not implemented on this platform");
#else
# error Unknown architecture
#endif
@ -941,294 +859,58 @@ std::string fs_get_cache_file(const std::string & filename) {
return cache_directory + filename;
}
std::vector<common_file_info> fs_list(const std::string & path, bool include_directories) {
std::vector<common_file_info> files;
if (path.empty()) return files;
std::filesystem::path dir(path);
if (!std::filesystem::exists(dir) || !std::filesystem::is_directory(dir)) {
return files;
}
for (const auto & entry : std::filesystem::directory_iterator(dir)) {
try {
// Only include regular files (skip directories)
const auto & p = entry.path();
if (std::filesystem::is_regular_file(p)) {
common_file_info info;
info.path = p.string();
info.name = p.filename().string();
info.is_dir = false;
try {
info.size = static_cast<size_t>(std::filesystem::file_size(p));
} catch (const std::filesystem::filesystem_error &) {
info.size = 0;
}
files.push_back(std::move(info));
} else if (include_directories && std::filesystem::is_directory(p)) {
common_file_info info;
info.path = p.string();
info.name = p.filename().string();
info.size = 0; // Directories have no size
info.is_dir = true;
files.push_back(std::move(info));
}
} catch (const std::filesystem::filesystem_error &) {
// skip entries we cannot inspect
continue;
}
}
return files;
}
//
// TTY utils
//
bool tty_can_use_colors() {
// Check NO_COLOR environment variable (https://no-color.org/)
if (const char * no_color = std::getenv("NO_COLOR")) {
if (no_color[0] != '\0') {
return false;
}
}
// Check TERM environment variable
if (const char * term = std::getenv("TERM")) {
if (std::strcmp(term, "dumb") == 0) {
return false;
}
}
// Check if stdout and stderr are connected to a terminal
// We check both because log messages can go to either
bool stdout_is_tty = isatty(fileno(stdout));
bool stderr_is_tty = isatty(fileno(stderr));
return stdout_is_tty || stderr_is_tty;
}
//
// Model utils
//
// TODO: move to common/sampling
static void common_init_sampler_from_model(
const llama_model * model,
common_params_sampling & sparams) {
const uint64_t config = sparams.user_sampling_config;
auto get_int32 = [&](const char * key, int32_t & dst, uint64_t user_config) {
if (config & user_config) {
return;
}
char buf[64] = {0};
if (llama_model_meta_val_str(model, key, buf, sizeof(buf)) > 0) {
char * end = nullptr;
int32_t v = strtol(buf, &end, 10);
if (end && end != buf) {
dst = v;
}
}
};
auto get_float = [&](const char * key, float & dst, uint64_t user_config) {
if (config & user_config) {
return;
}
char buf[128] = {0};
if (llama_model_meta_val_str(model, key, buf, sizeof(buf)) > 0) {
char * end = nullptr;
float v = strtof(buf, &end);
if (end && end != buf) {
dst = v;
}
}
};
// Sampling sequence
if (!(config & common_params_sampling_config::COMMON_PARAMS_SAMPLING_CONFIG_SAMPLERS)) {
char buf[512] = {0};
if (llama_model_meta_val_str(model, llama_model_meta_key_str(LLAMA_MODEL_META_KEY_SAMPLING_SEQUENCE), buf, sizeof(buf)) > 0) {
const std::vector<std::string> sampler_names = string_split<std::string>(std::string(buf), ';');
if (!sampler_names.empty()) {
sparams.samplers = common_sampler_types_from_names(sampler_names, true);
}
}
}
get_int32(llama_model_meta_key_str(LLAMA_MODEL_META_KEY_SAMPLING_TOP_K), sparams.top_k, common_params_sampling_config::COMMON_PARAMS_SAMPLING_CONFIG_TOP_K);
get_float(llama_model_meta_key_str(LLAMA_MODEL_META_KEY_SAMPLING_TOP_P), sparams.top_p, common_params_sampling_config::COMMON_PARAMS_SAMPLING_CONFIG_TOP_P);
get_float(llama_model_meta_key_str(LLAMA_MODEL_META_KEY_SAMPLING_MIN_P), sparams.min_p, common_params_sampling_config::COMMON_PARAMS_SAMPLING_CONFIG_MIN_P);
get_float(llama_model_meta_key_str(LLAMA_MODEL_META_KEY_SAMPLING_XTC_PROBABILITY), sparams.xtc_probability, common_params_sampling_config::COMMON_PARAMS_SAMPLING_CONFIG_XTC_PROBABILITY);
get_float(llama_model_meta_key_str(LLAMA_MODEL_META_KEY_SAMPLING_XTC_THRESHOLD), sparams.xtc_threshold, common_params_sampling_config::COMMON_PARAMS_SAMPLING_CONFIG_XTC_THRESHOLD);
get_float(llama_model_meta_key_str(LLAMA_MODEL_META_KEY_SAMPLING_TEMP), sparams.temp, common_params_sampling_config::COMMON_PARAMS_SAMPLING_CONFIG_TEMP);
get_int32(llama_model_meta_key_str(LLAMA_MODEL_META_KEY_SAMPLING_PENALTY_LAST_N), sparams.penalty_last_n, common_params_sampling_config::COMMON_PARAMS_SAMPLING_CONFIG_PENALTY_LAST_N);
get_float(llama_model_meta_key_str(LLAMA_MODEL_META_KEY_SAMPLING_PENALTY_REPEAT), sparams.penalty_repeat, common_params_sampling_config::COMMON_PARAMS_SAMPLING_CONFIG_PENALTY_REPEAT);
get_int32(llama_model_meta_key_str(LLAMA_MODEL_META_KEY_SAMPLING_MIROSTAT), sparams.mirostat, common_params_sampling_config::COMMON_PARAMS_SAMPLING_CONFIG_MIROSTAT);
get_float(llama_model_meta_key_str(LLAMA_MODEL_META_KEY_SAMPLING_MIROSTAT_TAU), sparams.mirostat_tau, common_params_sampling_config::COMMON_PARAMS_SAMPLING_CONFIG_MIROSTAT_TAU);
get_float(llama_model_meta_key_str(LLAMA_MODEL_META_KEY_SAMPLING_MIROSTAT_ETA), sparams.mirostat_eta, common_params_sampling_config::COMMON_PARAMS_SAMPLING_CONFIG_MIROSTAT_ETA);
}
struct common_init_result::impl {
impl() = default;
~impl() = default;
// note: the order in which model, context, etc. are declared matters because their destructors will be called bottom-to-top
llama_model_ptr model;
llama_context_ptr context;
std::vector<llama_adapter_lora_ptr> lora;
std::vector<common_sampler_ptr> samplers;
std::vector<llama_sampler_seq_config> samplers_seq_config;
};
common_init_result::common_init_result(common_params & params) :
pimpl(new impl{}) {
struct common_init_result common_init_from_params(common_params & params) {
common_init_result iparams;
auto mparams = common_model_params_to_llama(params);
auto cparams = common_context_params_to_llama(params);
if (params.fit_params) {
LOG_INF("%s: fitting params to device memory, for bugs during this step try to reproduce them with -fit off, or provide --verbose logs if the bug only occurs with -fit on\n", __func__);
llama_params_fit(params.model.path.c_str(), &mparams, &cparams,
params.tensor_split,
params.tensor_buft_overrides.data(),
params.fit_params_target.data(),
params.fit_params_min_ctx,
params.verbosity >= 4 ? GGML_LOG_LEVEL_DEBUG : GGML_LOG_LEVEL_ERROR);
}
llama_model * model = llama_model_load_from_file(params.model.path.c_str(), mparams);
if (model == NULL) {
return;
LOG_ERR("%s: failed to load model '%s'\n", __func__, params.model.path.c_str());
return iparams;
}
pimpl->model.reset(model);
const llama_vocab * vocab = llama_model_get_vocab(model);
// load and optionally apply lora adapters (must be loaded before context creation)
for (auto & la : params.lora_adapters) {
llama_adapter_lora_ptr lora;
lora.reset(llama_adapter_lora_init(model, la.path.c_str()));
if (lora == nullptr) {
LOG_ERR("%s: failed to load lora adapter '%s'\n", __func__, la.path.c_str());
pimpl->model.reset(model);
return;
if (params.reranking) {
bool ok = true;
if (llama_vocab_bos(vocab) == LLAMA_TOKEN_NULL) {
LOG_WRN("%s: warning: vocab does not have a BOS token, reranking will not work\n", __func__);
ok = false;
}
char buf[1024];
la.ptr = lora.get();
llama_adapter_meta_val_str(la.ptr, "adapter.lora.task_name", buf, sizeof(buf));
la.task_name = buf;
llama_adapter_meta_val_str(la.ptr, "adapter.lora.prompt_prefix", buf, sizeof(buf));
la.prompt_prefix = buf;
pimpl->lora.emplace_back(std::move(lora)); // copy to list of loaded adapters
}
if (llama_vocab_eos(vocab) == LLAMA_TOKEN_NULL) {
LOG_WRN("%s: warning: vocab does not have an EOS token, reranking will not work\n", __func__);
ok = false;
}
// updates params.sampling
// TODO: fix naming
common_init_sampler_from_model(model, params.sampling);
if (llama_vocab_sep(vocab) == LLAMA_TOKEN_NULL) {
LOG_WRN("%s: warning: vocab does not have a SEP token, reranking will not work\n", __func__);
ok = false;
}
if (params.sampling.ignore_eos && llama_vocab_eos(vocab) == LLAMA_TOKEN_NULL) {
LOG_WRN("%s: warning: vocab does not have an EOS token, ignoring --ignore-eos\n", __func__);
params.sampling.ignore_eos = false;
}
if (!ok) {
llama_model_free(model);
// initialize once
for (llama_token i = 0; i < llama_vocab_n_tokens(vocab); i++) {
if (llama_vocab_is_eog(vocab, i)) {
LOG_INF("%s: added %s logit bias = %f\n", __func__, common_token_to_piece(vocab, i).c_str(), -INFINITY);
params.sampling.logit_bias_eog.push_back({i, -INFINITY});
return iparams;
}
}
if (params.sampling.ignore_eos) {
// add EOG biases to the active set of logit biases
params.sampling.logit_bias.insert(
params.sampling.logit_bias.end(),
params.sampling.logit_bias_eog.begin(), params.sampling.logit_bias_eog.end());
}
//if (params.sampling.penalty_last_n == -1) {
// LOG_INF("%s: setting penalty_last_n to ctx_size = %d\n", __func__, llama_n_ctx(lctx));
// params.sampling.penalty_last_n = llama_n_ctx(lctx);
//}
//if (params.sampling.dry_penalty_last_n == -1) {
// LOG_INF("%s: setting dry_penalty_last_n to ctx_size = %d\n", __func__, llama_n_ctx(lctx));
// params.sampling.dry_penalty_last_n = llama_n_ctx(lctx);
//}
// init the backend samplers as part of the context creation
pimpl->samplers.resize(cparams.n_seq_max);
pimpl->samplers_seq_config.resize(cparams.n_seq_max);
for (int i = 0; i < (int) cparams.n_seq_max; ++i) {
pimpl->samplers[i].reset(common_sampler_init(model, params.sampling));
pimpl->samplers_seq_config[i] = { i, common_sampler_get(pimpl->samplers[i].get()) };
}
if (params.sampling.backend_sampling) {
cparams.samplers = pimpl->samplers_seq_config.data();
cparams.n_samplers = pimpl->samplers_seq_config.size();
}
auto cparams = common_context_params_to_llama(params);
llama_context * lctx = llama_init_from_model(model, cparams);
if (lctx == NULL) {
LOG_ERR("%s: failed to create context with model '%s'\n", __func__, params.model.path.c_str());
return;
llama_model_free(model);
return iparams;
}
pimpl->context.reset(lctx);
}
llama_model * common_init_result::model() {
return pimpl->model.get();
}
llama_context * common_init_result::context() {
return pimpl->context.get();
}
common_sampler * common_init_result::sampler(llama_seq_id seq_id) {
return pimpl->samplers[seq_id].get();
}
void common_init_result::reset_samplers() {
for (int i = 0; i < (int) pimpl->samplers.size(); ++i) {
llama_sampler_reset(common_sampler_get(pimpl->samplers[i].get()));
}
}
std::vector<llama_adapter_lora_ptr> & common_init_result::lora() {
return pimpl->lora;
}
common_init_result_ptr common_init_from_params(common_params & params) {
common_init_result_ptr res(new common_init_result(params));
llama_model * model = res->model();
if (model == NULL) {
LOG_ERR("%s: failed to load model '%s'\n", __func__, params.model.path.c_str());
return res;
}
llama_context * lctx = res->context();
if (lctx == NULL) {
LOG_ERR("%s: failed to create context with model '%s'\n", __func__, params.model.path.c_str());
return res;
}
const llama_vocab * vocab = llama_model_get_vocab(model);
if (params.ctx_shift && !llama_memory_can_shift(llama_get_memory(lctx))) {
if (params.ctx_shift && !llama_kv_self_can_shift(lctx)) {
LOG_WRN("%s: KV cache shifting is not supported for this context, disabling KV cache shifting\n", __func__);
params.ctx_shift = false;
}
@ -1239,7 +921,10 @@ common_init_result_ptr common_init_from_params(common_params & params) {
const auto cvec = common_control_vector_load(params.control_vectors);
if (cvec.n_embd == -1) {
return res;
llama_free(lctx);
llama_model_free(model);
return iparams;
}
int err = llama_apply_adapter_cvec(
@ -1250,38 +935,56 @@ common_init_result_ptr common_init_from_params(common_params & params) {
params.control_vector_layer_start,
params.control_vector_layer_end);
if (err) {
return res;
llama_free(lctx);
llama_model_free(model);
return iparams;
}
}
if (llama_pooling_type(lctx) == LLAMA_POOLING_TYPE_RANK) {
bool ok = true;
if (llama_vocab_bos(vocab) == LLAMA_TOKEN_NULL) {
LOG_WRN("%s: warning: vocab does not have a BOS token, reranking will not work\n", __func__);
ok = false;
// load and optionally apply lora adapters
for (auto & la : params.lora_adapters) {
llama_adapter_lora_ptr lora;
lora.reset(llama_adapter_lora_init(model, la.path.c_str()));
if (lora == nullptr) {
LOG_ERR("%s: failed to apply lora adapter '%s'\n", __func__, la.path.c_str());
llama_free(lctx);
llama_model_free(model);
return iparams;
}
bool has_eos = llama_vocab_eos(vocab) != LLAMA_TOKEN_NULL;
bool has_sep = llama_vocab_sep(vocab) != LLAMA_TOKEN_NULL;
bool has_rerank_prompt = llama_model_chat_template(model, "rerank") != NULL;
if (!has_eos && !has_sep && !has_rerank_prompt) {
LOG_WRN("%s: warning: vocab does not have an EOS token, SEP token, or rerank prompt. Reranking will not work\n", __func__);
ok = false;
} else if (!has_eos) {
LOG_WRN("%s: warning: vocab does not have an EOS token, using SEP token as fallback\n", __func__);
}
if (!ok) {
return res;
}
la.ptr = lora.get();
iparams.lora.emplace_back(std::move(lora)); // copy to list of loaded adapters
}
if (!params.lora_init_without_apply) {
common_set_adapter_lora(lctx, params.lora_adapters);
}
if (params.sampling.ignore_eos && llama_vocab_eos(vocab) == LLAMA_TOKEN_NULL) {
LOG_WRN("%s: warning: vocab does not have an EOS token, ignoring --ignore-eos\n", __func__);
params.sampling.ignore_eos = false;
}
if (params.sampling.ignore_eos) {
for (llama_token i = 0; i < llama_vocab_n_tokens(vocab); i++) {
if (llama_vocab_is_eog(vocab, i)) {
LOG_INF("%s: added %s logit bias = %f\n", __func__, common_token_to_piece(lctx, i).c_str(), -INFINITY);
params.sampling.logit_bias.push_back({i, -INFINITY});
}
}
}
if (params.sampling.penalty_last_n == -1) {
LOG_INF("%s: setting penalty_last_n to ctx_size = %d\n", __func__, llama_n_ctx(lctx));
params.sampling.penalty_last_n = llama_n_ctx(lctx);
}
if (params.sampling.dry_penalty_last_n == -1) {
LOG_INF("%s: setting dry_penalty_last_n to ctx_size = %d\n", __func__, llama_n_ctx(lctx));
params.sampling.dry_penalty_last_n = llama_n_ctx(lctx);
}
if (params.warmup) {
LOG_WRN("%s: warming up the model with an empty run - please wait ... (--no-warmup to disable)\n", __func__);
@ -1314,19 +1017,17 @@ common_init_result_ptr common_init_from_params(common_params & params) {
if (llama_model_has_decoder(model)) {
llama_decode(lctx, llama_batch_get_one(tmp.data(), std::min(tmp.size(), (size_t) params.n_batch)));
}
llama_memory_clear(llama_get_memory(lctx), true);
llama_kv_self_clear(lctx);
llama_synchronize(lctx);
llama_perf_context_reset(lctx);
llama_set_warmup(lctx, false);
// reset samplers to reset RNG state after warmup to the seeded state
res->reset_samplers();
}
return res;
}
iparams.model.reset(model);
iparams.context.reset(lctx);
common_init_result::~common_init_result() = default;
return iparams;
}
std::string get_model_endpoint() {
const char * model_endpoint_env = getenv("MODEL_ENDPOINT");
@ -1336,9 +1037,7 @@ std::string get_model_endpoint() {
std::string model_endpoint = "https://huggingface.co/";
if (endpoint_env) {
model_endpoint = endpoint_env;
if (model_endpoint.back() != '/') {
model_endpoint += '/';
}
if (model_endpoint.back() != '/') model_endpoint += '/';
}
return model_endpoint;
}
@ -1359,16 +1058,16 @@ struct llama_model_params common_model_params_to_llama(common_params & params) {
mparams.devices = params.devices.data();
}
mparams.n_gpu_layers = params.n_gpu_layers;
if (params.n_gpu_layers != -1) {
mparams.n_gpu_layers = params.n_gpu_layers;
}
mparams.main_gpu = params.main_gpu;
mparams.split_mode = params.split_mode;
mparams.tensor_split = params.tensor_split;
mparams.use_mmap = params.use_mmap;
mparams.use_direct_io = params.use_direct_io;
mparams.use_mlock = params.use_mlock;
mparams.check_tensors = params.check_tensors;
mparams.use_extra_bufts = !params.no_extra_bufts;
mparams.no_host = params.no_host;
if (params.kv_overrides.empty()) {
mparams.kv_overrides = NULL;
@ -1384,9 +1083,6 @@ struct llama_model_params common_model_params_to_llama(common_params & params) {
mparams.tensor_buft_overrides = params.tensor_buft_overrides.data();
}
mparams.progress_callback = params.load_progress_callback;
mparams.progress_callback_user_data = params.load_progress_callback_user_data;
return mparams;
}
@ -1400,6 +1096,7 @@ struct llama_context_params common_context_params_to_llama(const common_params &
cparams.n_threads = params.cpuparams.n_threads;
cparams.n_threads_batch = params.cpuparams_batch.n_threads == -1 ?
params.cpuparams.n_threads : params.cpuparams_batch.n_threads;
cparams.logits_all = params.logits_all;
cparams.embeddings = params.embedding;
cparams.rope_scaling_type = params.rope_scaling_type;
cparams.rope_freq_base = params.rope_freq_base;
@ -1411,14 +1108,17 @@ struct llama_context_params common_context_params_to_llama(const common_params &
cparams.yarn_orig_ctx = params.yarn_orig_ctx;
cparams.pooling_type = params.pooling_type;
cparams.attention_type = params.attention_type;
cparams.flash_attn_type = params.flash_attn_type;
cparams.defrag_thold = params.defrag_thold;
cparams.cb_eval = params.cb_eval;
cparams.cb_eval_user_data = params.cb_eval_user_data;
cparams.offload_kqv = !params.no_kv_offload;
cparams.flash_attn = params.flash_attn;
cparams.no_perf = params.no_perf;
cparams.op_offload = !params.no_op_offload;
cparams.swa_full = params.swa_full;
cparams.kv_unified = params.kv_unified;
if (params.reranking) {
cparams.embeddings = true;
cparams.pooling_type = LLAMA_POOLING_TYPE_RANK;
}
cparams.type_k = params.cache_type_k;
cparams.type_v = params.cache_type_v;
@ -1552,9 +1252,6 @@ std::vector<llama_token> common_tokenize(
int n_tokens = text.length() + 2 * add_special;
std::vector<llama_token> result(n_tokens);
n_tokens = llama_tokenize(vocab, text.data(), text.length(), result.data(), result.size(), add_special, parse_special);
if (n_tokens == std::numeric_limits<int32_t>::min()) {
throw std::runtime_error("Tokenization failed: input text too large, tokenization result exceeds int32_t limit");
}
if (n_tokens < 0) {
result.resize(-n_tokens);
int check = llama_tokenize(vocab, text.data(), text.length(), result.data(), result.size(), add_special, parse_special);
@ -1609,6 +1306,81 @@ std::string common_detokenize(const struct llama_vocab * vocab, const std::vecto
return text;
}
//
// KV cache utils
//
void common_kv_cache_dump_view(const llama_kv_cache_view & view, int row_size) {
static const char slot_chars[] = ".123456789ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz+";
printf("=== Dumping KV cache. total cells %d, max sequences per cell %d, populated cells %d, total tokens in cache %d, largest empty slot=%d @ %d",
view.n_cells, view.n_seq_max, view.used_cells, view.token_count, view.max_contiguous, view.max_contiguous_idx);
llama_kv_cache_view_cell * c_curr = view.cells;
llama_seq_id * cs_curr = view.cells_sequences;
for (int i = 0; i < view.n_cells; i++, c_curr++, cs_curr += view.n_seq_max) {
if (i % row_size == 0) {
printf("\n%5d: ", i);
}
int seq_count = 0;
for (int j = 0; j < view.n_seq_max; j++) {
if (cs_curr[j] >= 0) { seq_count++; }
}
putchar(slot_chars[std::min(sizeof(slot_chars) - 2, size_t(seq_count))]);
}
printf("\n=== Done dumping\n");
}
void common_kv_cache_dump_view_seqs(const llama_kv_cache_view & view, int row_size) {
static const char slot_chars[] = "0123456789ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz";
printf("=== Dumping KV cache. total cells %d, max sequences per cell %d, populated cells %d, total tokens in cache %d, largest empty slot=%d @ %d\n",
view.n_cells, view.n_seq_max, view.used_cells, view.token_count, view.max_contiguous, view.max_contiguous_idx);
std::unordered_map<llama_seq_id, size_t> seqs;
llama_kv_cache_view_cell * c_curr = view.cells;
llama_seq_id * cs_curr = view.cells_sequences;
for (int i = 0; i < view.n_cells; i++, c_curr++, cs_curr += view.n_seq_max) {
for (int j = 0; j < view.n_seq_max; j++) {
if (cs_curr[j] < 0) { continue; }
if (seqs.find(cs_curr[j]) == seqs.end()) {
if (seqs.size() + 1 >= sizeof(slot_chars)) { break; }
const size_t sz = seqs.size();
seqs[cs_curr[j]] = sz;
}
}
if (seqs.size() + 1 >= sizeof(slot_chars)) { break; }
}
printf("=== Sequence legend: ");
for (const auto & it : seqs) {
printf("%zu=%d, ", it.second, it.first);
}
printf("'+'=other sequence ids");
c_curr = view.cells;
cs_curr = view.cells_sequences;
for (int i = 0; i < view.n_cells; i++, c_curr++, cs_curr += view.n_seq_max) {
if (i % row_size == 0) {
printf("\n%5d: ", i);
}
for (int j = 0; j < view.n_seq_max; j++) {
if (cs_curr[j] >= 0) {
const auto & it = seqs.find(cs_curr[j]);
putchar(it != seqs.end() ? int(slot_chars[it->second]) : '+');
} else {
putchar('.');
}
}
putchar(' ');
}
printf("\n=== Done dumping\n");
}
//
// Embedding utils
//
@ -1793,73 +1565,3 @@ common_control_vector_data common_control_vector_load(const std::vector<common_c
return result;
}
ggml_opt_dataset_t common_opt_dataset_init(struct llama_context * ctx, const std::vector<llama_token> & tokens, int64_t stride) {
const int64_t ne_datapoint = llama_n_ctx(ctx);
const int64_t ndata = (tokens.size() - ne_datapoint - 1) / stride;
ggml_opt_dataset_t result = ggml_opt_dataset_init(
GGML_TYPE_I32, GGML_TYPE_I32, ne_datapoint, ne_datapoint, ndata, /*ndata_shard =*/ 1);
llama_token * data = (llama_token *) ggml_opt_dataset_data(result)->data;
llama_token * labels = (llama_token *) ggml_opt_dataset_labels(result)->data;
for (int64_t idata = 0; idata < ndata; ++idata) {
memcpy(data + idata*ne_datapoint, tokens.data() + idata*stride + 0, ne_datapoint*sizeof(llama_token));
memcpy(labels + idata*ne_datapoint, tokens.data() + idata*stride + 1, ne_datapoint*sizeof(llama_token));
}
return result;
}
ggml_opt_optimizer_params common_opt_lr_pars(void * userdata) {
ggml_opt_optimizer_params result = ggml_opt_get_default_optimizer_params(nullptr);
const lr_opt & d = *(lr_opt *) userdata;
result.adamw.alpha = result.sgd.alpha = d.get_lr(d.epoch);
result.sgd.wd = result.adamw.wd = d.wd;
return result;
}
// TODO make all command line args case-insensitive
static inline bool eq_case_insensitive(char const* a, char const* b) {
return !
#if defined(_MSC_VER)
_stricmp
#else
strcasecmp
#endif // defined(_MSC_VER)
(a, b);
}
enum ggml_opt_optimizer_type common_opt_get_optimizer(const char * n) {
if (eq_case_insensitive("adamw", n)) {
return GGML_OPT_OPTIMIZER_TYPE_ADAMW;
}
if (eq_case_insensitive("sgd", n)) {
return GGML_OPT_OPTIMIZER_TYPE_SGD;
}
return GGML_OPT_OPTIMIZER_TYPE_COUNT;
}
// TODO simplify to use just log and exp
static float const k_log_2 = std::log(2.f);
void lr_opt::init() {
if (lr_min > 0 && lr_min < lr0) {
float nhalf = std::log(lr0 / lr_min) / k_log_2;
float e = epochs;
if (decay_epochs > 0 && decay_epochs < e) {
e = decay_epochs;
} else {
decay_epochs = e;
}
scale_epoch = nhalf / e;
}
}
float lr_opt::get_lr(float epoch) const {
float r = lr_min <= 0 ? lr0 :
epoch >= decay_epochs ? lr_min :
lr0 * std::pow(0.5f, epoch * scale_epoch);
LOG_INF("epoch %.2g lr=%.2g\n", epoch, r);
return r;
}

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