Sadly the manifest does not list all required files, i honestly thought
it was the case
Without the files listed we don't have the sha256, so if the first file
is valid, and all others have the correct size, then we can assume we
are good and do the migration...
Here my test:
$ find /home/angt/.cache/llama.cpp
/home/angt/.cache/llama.cpp
/home/angt/.cache/llama.cpp/angt_test-split-model-stories260K_stories260K-f32-00002-of-00002.gguf
/home/angt/.cache/llama.cpp/angt_test-split-model-stories260K_stories260K-f32-00001-of-00002.gguf
/home/angt/.cache/llama.cpp/angt_test-split-model-stories260K_stories260K-f32-00001-of-00002.gguf.etag
/home/angt/.cache/llama.cpp/angt_test-split-model-stories260K_stories260K-f32-00002-of-00002.gguf.etag
/home/angt/.cache/llama.cpp/manifest=angt=test-split-model-stories260K=latest.json
$ build/bin/llama-server
================================================================================
WARNING: Migrating cache to HuggingFace cache directory
Old cache: /home/angt/.cache/llama.cpp/
New cache: /home/angt/.cache/huggingface/hub
This one-time migration moves models previously downloaded with -hf
from the legacy llama.cpp cache to the standard HuggingFace cache.
Models downloaded with --model-url are not affected.
================================================================================
migrate_file: migrated angt_test-split-model-stories260K_stories260K-f32-00001-of-00002.gguf -> /home/angt/.cache/huggingface/hub/models--angt--test-split-model-stories260K/snapshots/68c3ea2061e8c7688455fab07597dde0f4d7f0db/stories260K-f32-00001-of-00002.gguf
migrate_file: migrated angt_test-split-model-stories260K_stories260K-f32-00002-of-00002.gguf -> /home/angt/.cache/huggingface/hub/models--angt--test-split-model-stories260K/snapshots/68c3ea2061e8c7688455fab07597dde0f4d7f0db/stories260K-f32-00002-of-00002.gguf
migrate_old_cache_to_hf_cache: migration complete, deleting manifest: /home/angt/.cache/llama.cpp/manifest=angt=test-split-model-stories260K=latest.json
$ find /home/angt/.cache/llama.cpp /home/angt/.cache/huggingface
/home/angt/.cache/llama.cpp
/home/angt/.cache/huggingface
/home/angt/.cache/huggingface/hub
/home/angt/.cache/huggingface/hub/models--angt--test-split-model-stories260K
/home/angt/.cache/huggingface/hub/models--angt--test-split-model-stories260K/blobs
/home/angt/.cache/huggingface/hub/models--angt--test-split-model-stories260K/blobs/50d019817c2626eb9e8a41f361ff5bfa538757e6f708a3076cd3356354a75694
/home/angt/.cache/huggingface/hub/models--angt--test-split-model-stories260K/blobs/7b273e1dbfab11dc67dce479deb5923fef27c39cbf56a20b3a928a47b77dab3c
/home/angt/.cache/huggingface/hub/models--angt--test-split-model-stories260K/refs
/home/angt/.cache/huggingface/hub/models--angt--test-split-model-stories260K/refs/main
/home/angt/.cache/huggingface/hub/models--angt--test-split-model-stories260K/snapshots
/home/angt/.cache/huggingface/hub/models--angt--test-split-model-stories260K/snapshots/68c3ea2061e8c7688455fab07597dde0f4d7f0db
/home/angt/.cache/huggingface/hub/models--angt--test-split-model-stories260K/snapshots/68c3ea2061e8c7688455fab07597dde0f4d7f0db/stories260K-f32-00002-of-00002.gguf
/home/angt/.cache/huggingface/hub/models--angt--test-split-model-stories260K/snapshots/68c3ea2061e8c7688455fab07597dde0f4d7f0db/stories260K-f32-00001-of-00002.gguf
Signed-off-by: Adrien Gallouët <angt@huggingface.co>
Added check for dst_t to cuda_cast template for float
Restored ggml_cuda_ue4m3_to_fp32, changed vecdot ints to int32ts
Added CUDART/HIP Check and HIP/fp8 include
Added NVFP4 to Test-backend-ops
Added hip_fp8_e4m3 to __nv_fp8_e4m3 typedef
---------
Co-authored-by: Johannes Gäßler <johannesg@5d6.de>
* imatrix: fix crash when using --show-statistics with zero counts
Fixes division by zero that caused floating point exceptions when processing imatrix files with zero count values. Added checks to skip zero counts and handle empty activation vectors.
Fix for the bug #19190
* imatrix: lower log level for zero-count skip message to DBG
* Refactor CUDA 2D transpose implementation to support multiple kernel types and improve parameter handling
- Introduced a `conv2d_transpose_params` struct for better parameter management.
- Updated `conv2d_transpose_kernel` to be templated for different kernel types (float and half).
- Modified `ggml_cuda_conv_2d_transpose_p0` to handle both F16 and F32 kernel types.
- Enhanced test cases to validate functionality for both kernel types.
* Refactor test cases for 2D convolution transpose to support dynamic kernel types
- Updated `test_conv_transpose_2d` structure to improve parameter handling by reordering constructor arguments.
- Enhanced test case generation to iterate over kernel types, allowing for flexible testing of different configurations.
- Removed hardcoded kernel type instances in favor of a loop for better maintainability and scalability.
* Refactor ggml_compute_forward_conv_transpose_2d to support both F16 and F32 tensor types.
* Refactor conv2d transpose kernel to use a template for kernel type, enhancing flexibility for different data types.
Update test cases to include both F16 and F32 tensor types for comprehensive coverage.
* Update ggml/src/ggml-cuda/conv2d-transpose.cu
Co-authored-by: Aman Gupta <amangupta052@gmail.com>
* Update ggml/src/ggml-cpu/ggml-cpu.c
Co-authored-by: Aman Gupta <amangupta052@gmail.com>
* Refactor conv2d transpose implementation by removing the conv2d_transpose_params struct and dispatching with direct kernel launch.
* Enhance cpu conv2d transpose implementation by introducing a templated kernel type for improved flexibility with F16 and F32 data types.
---------
Co-authored-by: Aman Gupta <amangupta052@gmail.com>
* mtmd: llama.cpp DeepSeekOCR support
init commit
* loading sam tensors
* mtmd: fix vision model processing
* deepseek-ocr clip-vit model impl
* mtmd: add DeepSeek-OCR LM support with standard attention
* mtmd: successfully runs DeepSeek-OCR LM in llama-cli
* mtmd: Fix RoPE type for DeepSeek-OCR LM.
* loading LM
testing Vision model loading
* sam warmup working
* sam erroneous return corrected
* clip-vit: corrected cls_embd concat
* clip-vit: model convert qkv_proj split
* corrected combining of image encoders' results
* fix: update callback for ffn_moe_weighted and add callback for attn_out in deepseek2 model
* concat image_newline and image_seperator tokens
* visual_model warmup (technically) works
* window partitioning using standard ggml ops
* sam implementation without using CPU only ops
* clip: fixed warnings
* Merge branch 'sf/deepseek-ocr' of github.com:sfallah/llama.cpp into sf/deepseek-ocr
* mtmd: fix get_rel_pos
* mtmd: fixed the wrong scaler for get_rel_pos
* image encoding technically works but the output can't be checked singe image decoding fails
* mtmd: minor changed
* mtmd: add native resolution support
* - image encoding debugged
- issues fixed mainly related wrong config like n_patches etc.
- configs need to be corrected in the converter
* mtmd: correct token order
* - dynamic resizing
- changes are concerning PR https://github.com/sfallah/llama.cpp/pull/4
* mtmd: quick fix token order
* mtmd: fix danling pointer
* mtmd: SAM numerically works
* mtmd: debug CLIP-L (vit_pre_ln)
* mtmd: debug CLIP-L & first working DeepSeek-OCR model
* mtmd : add --dsocr-mode CLI argument for DeepSeek-OCR resolution control & all native resolution modes work
* mtmd: simplify SAM patch embedding
* mtmd: adapt Pillow image resizing function
* mtmd: simplify DeepSeek-OCR dynamic resolution preprocessing
* mtmd: remove --dsocr-mode argument
* mtmd: refactor code & remove unused helper functions
* mtmd: fix tensor names for image newlines and view separator
* clean up
* reverting automatically removed spaces
* reverting automatically removed spaces
* mtmd: fixed bad ocr check in Deepseek2 (LM)
* mtmd: support combined QKV projection in buid_vit
* using common build_attn in sam
* corrected code-branch when flash-attn disabled
enabling usage of --flash-attn option
* mtmd: minor fix
* minor formatting and style
* fixed flake8 lint issues
* minor editorconfig-check fixes
* minor editorconfig-check fixes
* mtmd: simplify get_rel_pos
* mtmd: make sam hparams configurable
* mtmd: add detailed comments for resize_bicubic_pillow
* mtmd: fixed wrong input setting
* mtmd: convert model in FP16
* mtmd: minor fix
* mtmd: remove tweak to llama-mtmd-cli & deepseek-ocr template
* fix: test-1.jpg ORC issue with small (640) resolution
setting min-resolution base (1024) max large (1280) for dynamic-resolution
* minor: editconfig-check fix
* merge with changes from https://github.com/ggml-org/llama.cpp/pull/17909
added new opt to tests.sh to disable flash-attn
* minor: editconfig-check fix
* testing deepseek-ocr
quick and dirty test script comparing results of Qwen2.5-VL vs DeepSeek-OCR
* quick and (potential) dirty merge with https://github.com/ggml-org/llama.cpp/pull/17909
* refactoring, one single builder function and static helpers
* added deepseek-ocr test to tests.sh
* minor formatting fixes
* check with fixed expected resutls
* minor formatting
* editorconfig-check fix
* merge with changes from https://github.com/ggml-org/llama.cpp/pull/18042
* minor
- added GLM-4.6V to big tests
- added missing deps for python test
* convert: minor fix
* mtmd: format code
* convert: quick fix
* convert: quick fix
* minor python formatting
* fixed merge build issue
* merge resolved
- fixed issues in convert
- tested several deepseek models
* minor fix
* minor
* Update convert_hf_to_gguf.py
Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com>
* - removed clip_is_deepseekocr
- removed redundant RESIZE_ALGO_BICUBIC_PILLOW resize-algo
- simplified image-preprocessing
- removed/simplified debug functions
* - cleaning commented out code
* fixing instabilities issues reintroducing resize_bicubic_pillow
* - use f16 model for deepseek-ocr test
- ignore llama-arch test for deepseek-ocr
* rename fc_w --> mm_fc_w
* add links to OCR discussion
* cleaner loading code
* add missing .weight to some tensors
* add default jinja template (to be used by server)
* move test model to ggml-org
* rolling back upscale change
* Update convert_hf_to_gguf.py
Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com>
---------
Co-authored-by: bluebread <hotbread70127@gmail.com>
Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com>
Co-authored-by: Xuan Son Nguyen <son@huggingface.co>
Co-authored-by: Xuan-Son Nguyen <thichthat@gmail.com>
The verbosity threshold was set at the end of common_params_parse_ex(),
after doing many things (like downloading files..)
Signed-off-by: Adrien Gallouët <angt@huggingface.co>
* scripts: hip: gcn-cdna-vgpr-check: fix parsing of vgpr counts when an amdclang Remark block is interlieved with another from a different process
* Return warning ignore
* obay pep8 inline double space before inline commets
* add # noqa: NP100 for other prints too
* Add script changes to cause autotrigger
* Add missing features to WoS scripts to achieve parity with ADB scripts
* Fix line-ending in run-mtmd.ps1
Signed-off-by: Max Krasnyansky <maxk@qti.qualcomm.com>
---------
Signed-off-by: Max Krasnyansky <maxk@qti.qualcomm.com>
Co-authored-by: Max Krasnyansky <maxk@qti.qualcomm.com>
* Remove make dependency
* Added option to specify Ninja generator
* use ninja-build as default for several CI
* Revert "use ninja-build as default for several CI"
This reverts commit f552c4559b.
* changed use plain string rather than arrays
* Enabled ninja build by default for experimentation
* ci: add run.sh to test conditions to trigger GitHub CI and self-hosted runners
Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>
* Enabled ninja build by default on self-hosted envs for experimentation
* ci: revert generator to ninja instead of ninja multi-config
Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>
* ci: install ninja-build for self-hosted workflows
Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>
* ci: revert ninja from self-hosted runners
Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>
* ci: missed one self-hosted step
Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>
* ci: fix windows ci errors from an errenous revert
Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>
* Added explicit build types for Ninja
Also reverted some needless change
* ci: use ninja multi-config for vulkan-x64 build
Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>
* added time command to measure build time
* Keeping some configs to use Ninja which show improvement
* minor fix based on review
Co-authored-by: Aaron Teo <taronaeo@gmail.com>
* ci: rm `time` from custom containers
Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>
---------
Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>
Co-authored-by: Aaron Teo <aaron.teo1@ibm.com>
Co-authored-by: Aaron Teo <taronaeo@gmail.com>
* common : add standard Hugging Face cache support
- Use HF API to find all files
- Migrate all manifests to hugging face cache at startup
Signed-off-by: Adrien Gallouët <angt@huggingface.co>
* Check with the quant tag
Signed-off-by: Adrien Gallouët <angt@huggingface.co>
* Cleanup
Signed-off-by: Adrien Gallouët <angt@huggingface.co>
* Improve error handling and report API errors
Signed-off-by: Adrien Gallouët <angt@huggingface.co>
* Restore common_cached_model_info and align mmproj filtering
Signed-off-by: Adrien Gallouët <angt@huggingface.co>
* Prefer main when getting cached ref
Signed-off-by: Adrien Gallouët <angt@huggingface.co>
* Use cached files when HF API fails
Signed-off-by: Adrien Gallouët <angt@huggingface.co>
* Use final_path..
Signed-off-by: Adrien Gallouët <angt@huggingface.co>
* Check all inputs
Signed-off-by: Adrien Gallouët <angt@huggingface.co>
---------
Signed-off-by: Adrien Gallouët <angt@huggingface.co>
* hex-dma: make chained dma the default to handle newer models
This also includes some new instrumentation that we can remove later.
* hexagon: add uint32 dump helper
* hexagon: use single-page VTCM allocation to avoid issues with large gather ops in ssm-conv
ssm-conv uses HVX gather instruction and that instruction cannot handle cases where the base+offset
spans page boundaries.
* hexagon: update ssm-conv to make base-addr compute a bit easier to read
* hex-dma: use 1d mode for reshaping, it supports sizes up to 24-bits (>16MB)
* hex-bin: fix incorrect stride logic
* hexagon: make sure repack buffs are dumped for verbose > 2
* hex-bin: consistently use dma_queue_push even for dummy dst transactions
* hex-dma: start using 2d-wide mode on v75 and up
The removes the need to deal with the 16-bit limitaion for the strides.
* hex-bin: cleanup kernel selection logic
* hex-bin: cleanup binary op core and fix transposed tensor handling
* snapdragon: update run-bench to use larger ubatch and fa-on
ihb2032
Adrien Gallouët
Michael Wand
SamareshSingh
Yihao Wang
Saba Fallah
uvos
Dowon
Aparna M P
Shreya Jain
Aman Gupta
Masato Nakasaka
Georgi Gerganov
Xuan-Son Nguyen
Francisco Herrera
Johannes Gäßler
Aleksander Grygier
Pascal
yikechayedan
Neo Zhang
Sigbjørn Skjæret
Ravi Panchumarthy
Alessandro de Oliveira Faria (A.K.A.CABELO)
BlueMöhre
nuri
Aaron Teo
Aldehir Rojas
Max Krasnyansky
lhez
las7
Davi Henrique Linhares
Geo Maciolek