shahondin1624
ddebb5ddf6
Squashes the entire TurboQuant KV-cache feature branch from https://github.com/TheTom/llama-cpp-turboquant (tip5aeb2fdbe) onto our master. Includes: TurboQuant KV-cache types (turbo2_0, turbo3_0, turbo4_0, tq3_1s, tq4_1s), GGML_OP_TURBO_WHT op, CUDA + Metal kernels (including TQ-rotated mul_mm path), CPU reference paths, HIP template instances, perplexity tooling, and 18 post-upstream-sync fixes (CVE-2026-21869 server clamp, HIP FA pool retention, n_head_v reshape, sparse-V CUDA gating, etc.). Conflict-resolution notes (review carefully before depending on these paths): - common/arg.cpp, common/speculative.cpp: master's refactored speculative API kept (params.speculative.types / ngram_mod struct, per-sinfo n_low/i_last). - ggml-cuda/fattn.cu: head-size exclusion lists unioned (now exclude both 192 and 640 alongside other sizes). - ggml-cuda/ggml-cuda.cu: both master's ADD/SUB/MUL/DIV F16 widening AND TurboQuant's GGML_OP_TURBO_WHT support cases kept. - ggml-metal-device.h/.cpp: master's new get_pipeline_mul_mv_ext signature (const ggml_tensor * op) kept; TurboQuant's get_pipeline_turbo_wht added. - ggml-metal-ops.cpp: TurboQuant's TQ-rotated mul_mm path preserved; non-TQ else-branch adapted to master's pipeline.nr0/nr1/nsg dispatch API. - ggml-vulkan.cpp: master's spec-constant-driven flash_attn pipeline iteration taken (over TurboQuant's CREATE_FA-per-type macro approach). TURBO3_0 added to the fa_kv_ok lambda for type validation. - ggml-vulkan/flash_attn_base.glsl, vulkan-shaders-gen.cpp: master's new spec-constant FA shader generation kept; TurboQuant's DATA_A_TURBO3_0 macro path NOT carried over. *** Vulkan TURBO3_0 flash-attention paths need re-implementation against the new spec-constant API. *** Vulkan TURBO3_0 inference will likely fail until that work is redone. Squash base:7fc1c4ef78(TheTom's last upstream merge point).
gguf
This is a Python package for writing binary files in the GGUF (GGML Universal File) format.
See convert_hf_to_gguf.py as an example for its usage.
Installation
pip install gguf
Optionally, you can install gguf with the extra 'gui' to enable the visual GGUF editor.
pip install gguf[gui]
API Examples/Simple Tools
examples/writer.py — Generates example.gguf in the current directory to demonstrate generating a GGUF file. Note that this file cannot be used as a model.
examples/reader.py — Extracts and displays key-value pairs and tensor details from a GGUF file in a readable format.
gguf/scripts/gguf_dump.py — Dumps a GGUF file's metadata to the console.
gguf/scripts/gguf_set_metadata.py — Allows changing simple metadata values in a GGUF file by key.
gguf/scripts/gguf_convert_endian.py — Allows converting the endianness of GGUF files.
gguf/scripts/gguf_new_metadata.py — Copies a GGUF file with added/modified/removed metadata values.
gguf/scripts/gguf_editor_gui.py — Allows for viewing, editing, adding, or removing metadata values within a GGUF file as well as viewing its tensors with a Qt interface.
Development
Maintainers who participate in development of this package are advised to install it in editable mode:
cd /path/to/llama.cpp/gguf-py
pip install --editable .
Note: This may require to upgrade your Pip installation, with a message saying that editable installation currently requires setup.py.
In this case, upgrade Pip to the latest:
pip install --upgrade pip
Automatic publishing with CI
There's a GitHub workflow to make a release automatically upon creation of tags in a specified format.
- Bump the version in
pyproject.toml. - Create a tag named
gguf-vx.x.xwherex.x.xis the semantic version number.
git tag -a gguf-v1.0.0 -m "Version 1.0 release"
- Push the tags.
git push origin --tags
Manual publishing
If you want to publish the package manually for any reason, you need to have twine and build installed:
pip install build twine
Then, follow these steps to release a new version:
- Bump the version in
pyproject.toml. - Build the package:
python -m build
- Upload the generated distribution archives:
python -m twine upload dist/*
Run Unit Tests
From root of this repository you can run this command to run all the unit tests
python -m unittest discover ./gguf-py -v
TODO
- Include conversion scripts as command line entry points in this package.