34fcc5a4ac
* First attempt * No permute during convert (fixes qk tensors), proper norm application. * RoPE = NeoX * Coherence! * Migrate xielu params from tensors to hyperparameters * Simple CUDA kernel * Revert stupid LLM refactorings * Chat template support * configchecker / flake8 errors * Reorder unary.cu * I do conclude that LLMs are, in fact, stupid. * Fix after merge * Final newline * Make xIELU an UNARY_OP * Final newline * Correctly account for parameter shift * Argh. * Update ggml/src/ggml-cpu/unary-ops.cpp Co-authored-by: Georgi Gerganov <ggerganov@gmail.com> * Refactor: remove unused methods, inline and factorize softplus, add const modifiers * Revert CUDA changes, implement xIELU as a separate OP * Pesky newline * Add float2half / half2float for F16 inputs/outputs * CUDA variants, attempt 2 * Actually, attempt 3 * Update ggml/src/ggml-cuda/unary.cu Co-authored-by: Johannes Gäßler <johannesg@5d6.de> * Missing convert header * Proper formula and reference for xIELU in the comments. * Modify unary-ops.cpp to add the functor-based logic besides the template system to retain optimizations * Apply suggestions from code review Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com> * Add tensor mappings for Apertus to global list instead * Fix lazy on scalars * Update ggml/src/ggml-cuda/unary.cu Co-authored-by: Johannes Gäßler <johannesg@5d6.de> * Add comment about the constraints on positive/negative alpha * Change `softplus` to `ggml_softplus` --------- Co-authored-by: Georgi Gerganov <ggerganov@gmail.com> Co-authored-by: Johannes Gäßler <johannesg@5d6.de> Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.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
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.