29a54f4b04
* Support MiMo DFlash draft conversion * Fix MiMo2 DFlash capture row pruning * Fix MiMo DFlash draft RoPE and value scale * Honor partial_rotary_factor in DFlash draft RoPE dim count The draft set rope.dimension_count to the full head_dim (128), ignoring the MiMo DFlash draft's partial_rotary_factor=0.5. The correct count is head_dim*partial_rotary_factor=64; the remaining dims are NoPE. With the full head_dim the upper half of each head receives position rotation it was never trained for, which roughly halves draft acceptance on code (~26% -> ~60% once corrected). RoPE base (5e6) and value scale (0.612) were already correct. * Filter weight-map shard discovery to files that exist get_model_part_names_from_weight_map() returned shard names straight from the index weight_map without checking they exist. A model dir with a stale model.safetensors.index.json but no safetensors shards would then set is_safetensors=True and skip the pytorch_model*.bin fallback, failing later when opening the missing files. Filter to shards present on disk so a stale index falls through to the other weight formats. * DFlash: store backbone_rotary_base in dedicated GGUF key backbone_rotary_base (the target model's RoPE theta used when encoding context K/V) was written to rope.freq_base, clobbering the draft model's own rope_theta. For MiMo this swapped 10000 → 5000000 in the draft attention path. Fix: write backbone_rotary_base to a dedicated dflash.backbone_rotary_base GGUF key and read it into hparams.dflash_backbone_rotary_base. In build_dflash_kv_cache, use target_freq_base (the new hparam when set, falling back to freq_base) for the context-K RoPE call. The draft model's own rope.freq_base is now set correctly from rope_theta. Existing MiMo DFlash GGUFs must be reconverted. --------- Co-authored-by: Joel Farthing <262452229+joelfarthing@users.noreply.github.com>
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
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.
scripts/gguf_dump.py — Dumps a GGUF file's metadata to the console.
scripts/gguf_set_metadata.py — Allows changing simple metadata values in a GGUF file by key.
scripts/gguf_convert_endian.py — Allows converting the endianness of GGUF files.
scripts/gguf_new_metadata.py — Copies a GGUF file with added/modified/removed metadata values.
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.