Oliver SimonsandSigbjørn Skjæret
68d20b884c
* WIP OCP FP8 E4M3 support * Fix python type-checker * Materialize input_scales also for FP8 when converting * Fix conversion of https://huggingface.co/RedHatAI/Qwen3.8-27B-NVFP4 1. Per row FP8 wrongly fell to NVFP4 conversion, as NVFP4 checked on dims alone. Also check on dtype for FP8 2. Need to reshape FP8 QKV projections scales in the same way that weights are reshaped * Allow remaining FP8 tensors to be dequantized during conversion * Allow tensor-strategy for FP8-only compressed-tensor ckpts * Fix and test gguf-py behavior for FP8_E4M3 * Disallow QKV-fusion for FP8 temporarily * Fix conversion of fused qkvz & FP8 for Qwen3-Next * Avoid fusing FP8 for --fuse-gate-up-exps as we may have different ws * Emit warnings when not fusing FP8 during conversion * More FP8 conversion fixes * Add supported for strided copies to/from FP8 in CPU * remove unneeded scratch buffer from FP8 cpu cpy/dup path * add explanatory comments and TODOs * Add dedicated encoder and decoder tests for FP8 * Whitelist ggml_op_get_rows in metal instead of blacklisting required to fix failing CI, and white-listing should be more future-proof than adding FP8 to the black-list https://github.com/ggml-org/llama.cpp/actions/runs/38433916498/job/115422880633?pr=27512 * Fix more conversion bugs * Defer weight materialization during conversion * Blacklist fp8 in metal backend instead of white-list * Adjust indents * Fix lint + execute tests * Add fast CPU kernel for F8_E4M3 * Conversion fixes * Fix remaining gaps * Enable tied weights with shared scales * Make mandatory-F32 rules apply to FP8 during conversion * Fix python type checks https://github.com/ggml-org/llama.cpp/actions/runs/39765670052/job/119780379595?pr=27512 * Fix kaleidai unit-test failures https://github.com/ggml-org/llama.cpp/actions/runs/39765670125/job/119780383150 * Relax numeric precision constraints for pre-check * Leave fast-FP8 CPU on RISC-V for follow-up We already exclude arm from the fast-path * Allow output scale tensors to be located in any gguf shard * Move test_conversion_fp8.py test execution to behavior-check.yaml * Apply batched suggestions from code review Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@huggingface.co> * Move mixed compressed-tensor logic into dequant_fp8 + add unit-tests for it * Install all requirements also on Windows for behavior-check Fixes https://github.com/ggml-org/llama.cpp/actions/runs/40535852590/job/122300758223?pr=27512 * Unmap lazy tensors before clean-up in Windows Should fix https://github.com/ggml-org/llama.cpp/actions/runs/40539797824/job/122314782459?pr=27512 * LF line endings https://github.com/ggml-org/llama.cpp/actions/runs/40539798168/job/122314791118?pr=27512 * Extract FP8 tests from llama-arch to its own test-fixture See https://github.com/ggml-org/llama.cpp/pull/27512#discussion_r4400628221 * Update gguf-py/gguf/scripts/gguf_convert_endian.py Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@huggingface.co> --------- Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@huggingface.co>
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.