* Add Maincoder model support
* Removed SPM model vocabulary setting and MOE related GGUF parameters
Removed trailing spaces from maincoder.cpp
* removed set_vocab
* added new line
* Fix formatting
* Add a new line for PEP8
* model: add Solar-Open model
* vocab: add solar-open to end eog blacklist
* model: add proper llm type
* chat: basic template for solar open
* typo: fix comment about vocab
* convert: sugested changes
* convert: suggested changes
* chat: change reasoning end tag for solar-open
* llama-chat: add solar-open template
ModernBERT but without `head.norm` so will currently fail to convert and run any other ModernBERT models, PRs with `head.norm` support welcome!
* constants and tensor mappings for modern bert support, model not supported yet but working on getting conversion to work for encoder only
* conversion now working, hf -> gguf
* working on support, now working on building graph
* some cleanup
* cleanup
* continuing
* correct tensor shape for qkv
* fixed tensor mappings and working on buildin graph
* tensor debugging now works -> (llama-eval-callback), instead of simulated gate split with views, GEGLU is now used which does exactly this
* cleanup
* cleanup
* cleanup
* more cleanup
* ubatch issues, the assert for checking equal seqs in llama-graph.cpp when building attention keeps failing, setting ubatch size to 1 when running llama-embedding with --ubatch-size 1 makes it work, but needs to be looked into more
* added cls token per previous modern bert attempt, still working on checking out the rest
* fixed pre tokenizer and still working through previous pr
* working through previous attemp, implimented more accurate conversion per previous attempt, added local sliding window attention that alternates every third layer
* fixed pre tokenizer
* working on swa with local and global alternating attention
* some cleanup and now fails on build attn
* starting to work, and some cleanup, currently failing on last layer construction in graph build
* alternating rope implemented and modern bert graph build succeeds
* fixed asser for equal ubatch seq
* cleanup
* added mask check in vocab
* fixed alternating rope, the hparams.rope_freq_base_train and hparams.rope_freq_base_train_swa were the same and i set them to correct values
* reuse variable
* removed repeat
* standard swa method can be used instead of a new enum being LLAMA_SWA_TYPE_LOCAL
* correct swa layer indexing, is supposed to be 0, 3, 6 ... instead of 1, 4, 7 ...
* more modular hparam setting
* replaced attn out norm with ffn_norm and cosine similarity between hf embds and llama.cpp embds went way up, from 0.05 to 0.24, replaced the cacheless kv with swa todo per the previous conversion
* Update gguf-py/gguf/tensor_mapping.py
Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com>
* Update convert_hf_to_gguf_update.py
Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com>
* Update src/llama-model.cpp
Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com>
* Update src/llama-vocab.cpp
Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com>
* Update src/llama-model.cpp
Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com>
* Update gguf-py/gguf/tensor_mapping.py
Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com>
* Update convert_hf_to_gguf.py
Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com>
* Update gguf-py/gguf/tensor_mapping.py
Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com>
* Update gguf-py/gguf/tensor_mapping.py
Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com>
* Update convert_hf_to_gguf.py
Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com>
* Update gguf-py/gguf/tensor_mapping.py
Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com>
* Update gguf-py/gguf/tensor_mapping.py
Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com>
* Update gguf-py/gguf/tensor_mapping.py
Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com>
* Update gguf-py/gguf/tensor_mapping.py
Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com>
* Update gguf-py/gguf/tensor_mapping.py
Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com>
* Update gguf-py/gguf/tensor_mapping.py
Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com>
* Update src/llama-graph.cpp
Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com>
* Update src/llama-arch.cpp
Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com>
* Update src/llama-model.cpp
Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com>
* Update src/llama-model.cpp
Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com>
* Update src/llama-model.cpp
Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com>
* Update src/llama-model.cpp
Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com>
* Update src/llama-model.cpp
Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com>
* removed redundant hparam set
* enums for model sizes
* conversion for modern-bert model supported rather than just granite-small
* Update src/llama-model.cpp
Co-authored-by: Gabe Goodhart <ghart@us.ibm.com>
* Update src/llama-model.cpp
Co-authored-by: Gabe Goodhart <ghart@us.ibm.com>
* fixed ordering of enum for freq_base_swa
* fixed where I added residual, now gives much much better embeddings~
* readded cacheless logic
* removing whitespace
* conversion now working for swa pattern - dense every n layers
* modern bert put into seperate src file
* removing whitespace
* fixed whitespace and newline errors in editorconfig job
* Update convert_hf_to_gguf.py
Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com>
* better naming convention, n_swa_pattern -> swa_period
* reusing sliding_window_pattern key rather than making new dense_every_n_layers key, and adding writing and reading support
* fixing pyright type-check fail
* Update convert_hf_to_gguf.py
Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com>
* Update gguf-py/gguf/gguf_writer.py
Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com>
* Update src/llama-hparams.h
Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com>
* Update src/llama-model-saver.cpp
Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com>
* Update src/models/modern-bert.cpp
Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com>
* Update src/models/modern-bert.cpp
Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com>
* Update src/models/modern-bert.cpp
Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com>
* Update gguf-py/gguf/gguf_writer.py
Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com>
* Update src/models/modern-bert.cpp
Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com>
* Update src/models/modern-bert.cpp
Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com>
* Update src/llama-model.cpp
Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com>
* Update src/llama-model-loader.cpp
Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com>
* Update src/llama-model-loader.cpp
Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com>
* Update src/llama-model-loader.cpp
Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com>
* added descriptions in llama-model
* fixed tensor mappings for conversion
* Update src/llama-model.cpp
Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com>
* Update src/llama-model.cpp
Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com>
* mapping name for size
* nits
* unused
---------
Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com>
Co-authored-by: Gabe Goodhart <ghart@us.ibm.com>
* convert ok
* no deepstack
* less new tensors
* cgraph ok
* add mrope for text model
* faster patch merger
* add GGML_ROPE_TYPE_MRNORM
* add support for metal
* move glm4v do dedicated graph
* convert: add norm_embd
* clip: add debugging fn
* working correctly
* fix style
* use bicubic
* fix mrope metal
* improve cpu
* convert to neox ordering on conversion
* revert backend changes
* force stop if using old weight
* support moe variant
* fix conversion
* fix convert (2)
* Update tools/mtmd/clip-graph.h
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
* process mrope_section on TextModel base class
* resolve conflict merge
---------
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
* llama : add support for NVIDIA Nemotron Nano 3
This commit adds support for the NVIDIA Nemotron Nano 3 model, enabling
the conversion and running of this model.
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
* llama: automatically fit args to free memory
llama-fit-params tool
* fix CI
* hints for bug reports, ensure no reallocation
* fix segfault with Vulkan
* add llama-fit-params to CI
* fix CI
* fix CI
* fix CI
* minor adjustments
* fix assignment of 1 dense layer
* fix logger not being reset on model load failure
* remove --n-gpu-layer hint on model load failure
* fix llama-fit-params verbosity
* fix edge case
* fix typo [no ci]
* Qwen3 Next - cleaned up version
* Whitespaces and stuff
* Correct minor errors
* Update src/llama-model.cpp
Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com>
* Misc. fixes.
* Clean up code, add missing hybrid qualifier
* Did someone transpose the SOLVE_TRI result matrix? Perhaps...
* Whitespace
* Proper tensors for cb calls
* Use llama-graph.h vertical alignment
* BROKEN: chunking
* Set new tensors as inputs.
* Proper chunk logic
* It's the circle of life...
* More shenanigans for n_seq > 1
* Nail in the coffin?
* Fix Windows build
* Eh, one fails on Windows, the other fails on Mac... just use general capture.
* quant : cleanup
* model : cleanup
* qwen3 : cleanup
* cont : cleanup
* cont : cleanup
* ggml : revert change
* qwen3 : cleanup
* cont : cleanup
* Readd cmath
* qwen3 : fix typo
* Update convert_hf_to_gguf.py
Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com>
* Usual suspects
* fix my bad suggestion
---------
Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com>
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
* Detect GigaChat3-10-A1.8B as deepseek lite
Hardcodes checking number of layers to detect if lite version of deepseek.
* Add commnent identifying deepseek lite variants
deepseek lite variants include DeepSeek-V2-Lite, GigaChat3-10B-A1.8B
* server : support unified context across slots
* cont : fix speculative decoding initialization
* context : fix n_ctx_per_seq computation
* server : purge slots one by one
* tests : add unified cache server tests
* llama : update per-seq context computation
* test-thread-safety : handle tiny training context of the input model
* server : fix server_tokens clear()
* server : use 4 slots + unified KV by default
* llama : add note about context size queries
* cont : update todos [no ci]
* context : do not cap the size of the context
* tests : adjust parameters to be CI friendlier
* context : add warning
* Added GGUF mappings for CogVLM model
* Add tensor mapping for CogVLM visual encoder
* Add CogVLM to conversion script, no vision part yet
* Added CogVLM vision model to conversion script
* Add graph for CogVLM CLIP model
* Add graph for CogVLM
* Fixes for CogVLM. Now compiles.
* Model now runs
* Fixes for cogvlm graph
* Account for graph context change after rebase
* Changes for whitespace
* Changes in convert script according to comments
* Switch CogVLM LLM graph to merged QKV tensor
* Use rope_type variable instead of direct definition
* Change CogVLM CLIP encoder to use SWIGLU
* Switch CogVLM CLIP to use merged QKV
* Apply rebase edits and remove ggml_cont call that is now unnecessary
* clean up
---------
Co-authored-by: Xuan Son Nguyen <son@huggingface.co>
* model: add support for extra bufs for all devices
* hexagon: add experimental ggml-hexagon backend for the Hexagon NPU
This commit introduces a new experimental backend `ggml-hexagon` with support for the Hexagon NPU.
Highlights:
- Supports Hexagon versions: v73, v75, v79, and v81
- Targets Android devices based on Snapdragon SoCs: Gen3, 8-Elite, and 8-Elite Gen5
- Supports Q4_0, Q8_0, MXFP4, and FP32 data types
- Implements core LLM ops: MUL_MAT/MUL_MAT_ID, ADD/SUB/MUL/ADD_ID, RMS_NORM, ROPE, GLU/SWIGLU, SOFTMAX
**Note:** This backend is experimental and may exhibit instability or limited performance across supported devices.
It is intended for early testing and feedback from llama.cpp/ggml developer and user community.
Co-Authored-By: Rajdeep Ganguly <rganguly@qti.qualcomm.com>
Co-Authored-By: Todor Boinovski <todorb@qti.qualcomm.com>
* hexagon: fix format checker errors
* hexagon: update readme and cmake presets
* ci: add android-ndk-build jobs that build plain ARM64 and Snapdragon versions
* hexagon: add simple graph optimizer for stacking MUL_MAT ops with the same input
* hexagon: move ADB helper scripts into scripts/snapdragon/adb
* hexagon: replace all f/printfs with GGML_LOG_...
* readme: add hexagon to the list supported backends
* hexagon: stack malmuts with quantized inputs only
* hexagon: add TODO for fixing issues in hexagon_graph_optimize
* hexagon: update to hex-sdk 6.4.0 and add scripts for running on QDC
* scripts: fix lint errors
* scripts: update qdc pytest script to make linter happy
* hexagon: add reduce sum in fp32
* hexagon: reduce number of vector stores in matmul output
* hexagon: remove the need for vdelta in reduce-multiply-x8
* hexagon: consistent use of reduce_sum_fp32 for row_sums
* hexagon: some more matmul optimizations and comments
Optimize cases where tensor dims are not multiple of 1024 (e.g in Qwen models).
We've handled those cases already but at a higher overhead.
* hexagon: update cmake presets
* hexagon: add OPMASK support for run-bench.sh wrapper
* hexagon: update to use GGML_BACKEND_API
* hexagon: remove unused logic for setting tensor flags for the views
* hexagon: add asserts to set/get_tensor to make sure we handle complete tensors
Same asserts as the CPU backend.
* hexagon: use cpy_tensor slow path for non-host buffers
* hexagon: error checks in the buffer allocator
* cmake: move include(extProj) under ggml-hexagon
* hexagon: don't forget to delete the backend on free
* hexagon: set/get_tensor size assert apply only to quantized tensors
* hexagon: reintroduce HEX_VERBOSE wrapper for GGML_LOG_DEBUG for now
GGML_LOG_DEBUG is always enabled for test-backend-ops and the output gets in the way.
Ideally we need a bit more finer log levels.
* docs: typos in hexagon developer docs (libggm-...)
* hexagon: overhaul error handling in the session/device allocation
this should handle all failure paths in the session allocation.
* hexagon: update cmake presets to enable fp16 vectors
* hexagon: remove unused time_usec function
* hexagon: don't forget to release buffer contexts
* hexagon: fixed indents in hvx-utils (missed clang-format auto-format failure)
* hexagon: remove custom can_repeat function and use ggml_can_repeat
---------
Co-authored-by: Rajdeep Ganguly <rganguly@qti.qualcomm.com>
Co-authored-by: Todor Boinovski <todorb@qti.qualcomm.com>
* add BailingMoeV2 support
* update llm types
* undo
* undo
* update llm types
* add model collection link
* update
* almost working
* correct group selection and rename n_group_exp
* avoid large top_k and use argmax instead for now
if we had something like argmax2 that would be equivalent, but this works fine until then
* poke
* skip group selection when there are no tokens
* fix 1T conversion
* hopefully fixed expert group selection
third time's the charm?
* make expert group selection generally available
The new LLaDA2Moe model uses this method too, make it generally available regardless of architecture.
* allow n_expert_groups to be 1 (Kimi K2)
* address review suggestions