Metadata-Version: 2.4
Name: gguf
Version: 0.17.1
Summary: Read and write ML models in GGUF for GGML
License-File: LICENSE
Keywords: ggml,gguf,llama.cpp
Author: GGML
Author-email: ggml@ggml.ai
Requires-Python: >=3.8
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Classifier: Programming Language :: Python :: 3.13
Classifier: Programming Language :: Python :: 3.14
Provides-Extra: gui
Requires-Dist: PySide6 (>=6.9,<7.0) ; (python_version >= "3.9" and python_version < "3.14") and (extra == "gui")
Requires-Dist: numpy (>=1.17)
Requires-Dist: pyyaml (>=5.1)
Requires-Dist: requests (>=2.25)
Requires-Dist: tqdm (>=4.27)
Project-URL: Homepage, https://ggml.ai
Project-URL: Repository, https://github.com/ggml-org/llama.cpp
Description-Content-Type: text/markdown

## gguf

This is a Python package for writing binary files in the [GGUF](https://github.com/ggml-org/ggml/pull/302)
(GGML Universal File) format.

See [convert_hf_to_gguf.py](https://github.com/ggml-org/llama.cpp/blob/master/convert_hf_to_gguf.py)
as an example for its usage.

## Installation
```sh
pip install gguf
```

Optionally, you can install gguf with the extra 'gui' to enable the visual GGUF editor.
```sh
pip install gguf[gui]
```

## API Examples/Simple Tools

[examples/writer.py](https://github.com/ggml-org/llama.cpp/blob/master/gguf-py/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](https://github.com/ggml-org/llama.cpp/blob/master/gguf-py/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](https://github.com/ggml-org/llama.cpp/blob/master/gguf-py/gguf/scripts/gguf_dump.py) — Dumps a GGUF file's metadata to the console.

[gguf/scripts/gguf_set_metadata.py](https://github.com/ggml-org/llama.cpp/blob/master/gguf-py/gguf/scripts/gguf_set_metadata.py) — Allows changing simple metadata values in a GGUF file by key.

[gguf/scripts/gguf_convert_endian.py](https://github.com/ggml-org/llama.cpp/blob/master/gguf-py/gguf/scripts/gguf_convert_endian.py) — Allows converting the endianness of GGUF files.

[gguf/scripts/gguf_new_metadata.py](https://github.com/ggml-org/llama.cpp/blob/master/gguf-py/gguf/scripts/gguf_new_metadata.py) — Copies a GGUF file with added/modified/removed metadata values.

[gguf/scripts/gguf_editor_gui.py](https://github.com/ggml-org/llama.cpp/blob/master/gguf-py/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:

```sh
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:

```sh
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.

1. Bump the version in `pyproject.toml`.
2. Create a tag named `gguf-vx.x.x` where `x.x.x` is the semantic version number.

```sh
git tag -a gguf-v1.0.0 -m "Version 1.0 release"
```

3. Push the tags.

```sh
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:

```sh
pip install build twine
```

Then, follow these steps to release a new version:

1. Bump the version in `pyproject.toml`.
2. Build the package:

```sh
python -m build
```

3. Upload the generated distribution archives:

```sh
python -m twine upload dist/*
```

## Run Unit Tests

From root of this repository you can run this command to run all the unit tests

```bash
python -m unittest discover ./gguf-py -v
```

## TODO
- [ ] Include conversion scripts as command line entry points in this package.

