7ce2c77f88
* gguf : add support for I64 and F64 arrays GGML currently does not support I64 or F64 arrays and they are not often used in machine learning, however if in the future the need arises, it would be nice to add them now, so that the types are next to the other types I8, I16, I32 in the enums, and it also reserves their type number. Furthermore, with this addition the GGUF format becomes very usable for most computational applications of NumPy (being compatible with the most common NumPy dtypes: i8, i16, i32, i64, f32, f64), providing a faster, and more versatile alternative to the `npz` format, and a simpler alternative to the `hdf5` format. The change in this PR seems small, not significantly increasing the maintenance burden. I tested this from Python using GGUFWriter/Reader and `gguf-dump`, as well as from C, everything seems to work. * Fix compiler warnings |
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gguf | ||
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README.md |
gguf
This is a Python package for writing binary files in the GGUF (GGML Universal File) format.
See convert-llama-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.
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.x
wherex.x.x
is 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/*
TODO
- Add tests
- Include conversion scripts as command line entry points in this package.