Main thing is that the default output filename will take this form {name}{parameters}{finetune}{version}{encoding}{kind} In addition this add and remove some entries in the KV store and adds a metadata class with automatic heuristics capability to derive some values based on model card content * No Change: - Internal GGUF Spec - `general.architecture` - `general.quantization_version` - `general.alignment` - `general.file_type` - General Model Details - `general.name` - `general.author` - `general.version` - `general.description` - Licensing details - `general.license` - Typically represents the converted GGUF repo (Unless made from scratch) - `general.url` - Model Source during conversion - `general.source.url` * Removed: - Model Source during conversion - `general.source.huggingface.repository` * Added: - General Model Details - `general.organization` - `general.finetune` - `general.basename` - `general.quantized_by` - `general.size_label` - Licensing details - `general.license.name` - `general.license.link` - Typically represents the converted GGUF repo (Unless made from scratch) - `general.doi` - `general.uuid` - `general.repo_url` - Model Source during conversion - `general.source.doi` - `general.source.uuid` - `general.source.repo_url` - Base Model Source - `general.base_model.count` - `general.base_model.{id}.name` - `general.base_model.{id}.author` - `general.base_model.{id}.version` - `general.base_model.{id}.organization` - `general.base_model.{id}.url` (Model Website/Paper) - `general.base_model.{id}.doi` - `general.base_model.{id}.uuid` - `general.base_model.{id}.repo_url` (Model Source Repository (git/svn/etc...)) - Array based KV stores - `general.tags` - `general.languages` - `general.datasets` --------- Co-authored-by: compilade <git@compilade.net> Co-authored-by: Xuan Son Nguyen <thichthat@gmail.com>
2.7 KiB
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.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/*
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.