llama.cpp/gguf-py
slaren 08a0c02060
ggml : mul_mat_id use the same tensor for all the experts (#6387)
* ggml : update mul_mat_id to use the same tensor for all the experts

* update cuda

* minor

* update metal

* update test-backend-ops

* fix cuda

* Update ggml-metal.m

Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>

* update convert.py

* update convert-hf-to-gguf.py

* update convert.py for mixtral hf models

* Update convert-hf-to-gguf.py

Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>

* cuda : support non-pow-2 number of experts

* allow quantize to work for split and merged experts models in the same way

* cleanup + disable mmap automatically with split tensors models

* update imatrix

* test-backend-ops : test qwen argsort

* update grok model loading

* llama : add merged experts tensors to the grok tensor map

* minor

* gguf : bump version

* fix quantizing of merged experts

* convert-hf-to-gguf.py : update grok (untested)

* make linter happy

* cuda/argsort : use shared memory instead of pool memory

* convert : fix grok tensor names

* metal : add support for non-pow-2 argsort

* llama : more loader cleanup, better error checking

* cuda : fix warning

* llama : still use mmap for loading old models, but copy the data to a host buffer

* add review note

* llama : remove ffn tensor counting + add sanity check

ggml-ci

* convert : fix handling of n_experts == None

ggml-ci

* imatrix : fix ncall counters

* llama : produce error if imatrix size does not match

* quantize : terminate on errors + trace logs

ggml-ci

* metal : pad shared memory to 16 bytes

---------

Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
2024-04-03 16:07:05 +03:00
..
examples gguf : add python reader example (#5216) 2024-02-13 19:56:38 +02:00
gguf ggml : mul_mat_id use the same tensor for all the experts (#6387) 2024-04-03 16:07:05 +03:00
scripts Respect tokenizer.ggml.add_bos_token value when tokenizing (#4040) 2023-11-16 19:14:37 -07:00
tests gguf-py: Refactor and allow reading/modifying existing GGUF files (#3981) 2023-11-11 08:04:50 +03:00
LICENSE gguf : make gguf pip-installable 2023-08-25 09:26:05 +03:00
pyproject.toml ggml : mul_mat_id use the same tensor for all the experts (#6387) 2024-04-03 16:07:05 +03:00
README.md gguf-py : fix broken link 2023-12-21 23:20:36 +02:00

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.

  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/*

TODO

  • Add tests
  • Include conversion scripts as command line entry points in this package.