llama.cpp/gguf-py
Gabe Goodhart 0d2ec43833
llama : support IBM Granite architecture (#9412)
* feat(gguf-py): Add Granite model and params to gguf-py

Branch: GraniteLM

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* feat(convert_hf_to_gguf): Add registration and param setup for Granite

Branch: GraniteLM

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* feat(llama.cpp): Add config parsing for Granite multiplier params

Branch: GraniteLM

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* feat(llama.cpp): First pass at full port of granite deviations from llama

Something is still not working right since the results are mostly terrible,
but on occasion it's producing relevant results at this point, so
_something_ is working.

Branch: GraniteLM

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* fix(llama.cpp): Determine granite language 3b instruct by vocab size

Branch: GraniteLM

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* fix(convert_hf_to_gguf): Use LlamaModel as base for GraniteModel

The defaults in LlamaModel are needed for Granite as well

Branch: GraniteLM

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* fix(llama.cpp): Switch Granite param names to use _scale for consistency

Other scalar multipliers are called *_scale, so this provides a more
consistent naming convention.

Branch: GraniteLM

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* fix(convert_hf_to_gguf/gguf-py): _multiplier -> _scale

The transformers names with _multiplier will now be converted to the _scale
equivalent during conversion.

Branch: GraniteLM

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* fix(llama.cpp): Use separate switch clause for granite in llm_load_hparams

Branch: GraniteLM

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

---------

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>
2024-09-17 09:44:58 +03:00
..
examples gguf-py : fix double call to add_architecture() (#8952) 2024-08-10 08:58:49 +03:00
gguf llama : support IBM Granite architecture (#9412) 2024-09-17 09:44:58 +03:00
scripts gguf_dump.py: fix markddown kv array print (#8588) 2024-07-20 17:35:25 +10:00
tests ggml-quants : ternary packing for TriLMs and BitNet b1.58 (#8151) 2024-09-05 21:48:47 -04:00
LICENSE gguf : make gguf pip-installable 2023-08-25 09:26:05 +03:00
pyproject.toml build(nix): Package gguf-py (#5664) 2024-09-02 14:21:01 +03:00
README.md convert-*.py: GGUF Naming Convention Refactor and Metadata Override Refactor (#7499) 2024-07-18 20:40:15 +10:00

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.

  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.
git tag -a gguf-v1.0.0 -m "Version 1.0 release"
  1. 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:

  1. Bump the version in pyproject.toml.
  2. Build the package:
python -m build
  1. 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.