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* feat: Add GGUF conversion for granitemoeshared Branch: GraniteMoEShared Signed-off-by: Gabe Goodhart <ghart@us.ibm.com> * feat: hparam and arch plumbing for granitemoeshared Branch: GraniteMoEShared Signed-off-by: Gabe Goodhart <ghart@us.ibm.com> * fix: Split MoE fused tensors for shared experts in conversion Branch: GraniteMoEShared Signed-off-by: Gabe Goodhart <ghart@us.ibm.com> * feat: First WIP cut at model arch in cpp The hparam and architecture plumbing should be correct, but the implementation of the shared experts seems to still be broken. Branch: GraniteMoEShared Signed-off-by: Gabe Goodhart <ghart@us.ibm.com> * fix: Cleaner (maybe more correct?) splitting for gate/up Branch: GraniteMoEShared Signed-off-by: Gabe Goodhart <ghart@us.ibm.com> * fix: Fix the input to the shared experts I had misread that the shared experts take the inputs _before_ the standard MoE layer and was feeding the output of the MoE to the shared experts. Branch: GraniteMoEShared Signed-off-by: Gabe Goodhart <ghart@us.ibm.com> * fix: Avoid architecture-specific checks for Granite MoE Shared This is a cleaner way that will allow more flexibility in architecture strings going forward. Branch: GraniteMoEShared Signed-off-by: Gabe Goodhart <ghart@us.ibm.com> * refactor: Split granite architectures out of llm_build_llama This helps de-clutter the llama-family graph construction and allows granite to diverge further (in preparation for Granite 4). NOTE: I removed the granite scale factors from llm_build_deci because they appear to only be there as copy-paste from llm_build_llama. The HF config does not seem to set those values: https://huggingface.co/Deci/DeciLM-7B/blob/main/config.json Branch: GraniteMoEShared Signed-off-by: Gabe Goodhart <ghart@us.ibm.com> * fix: Fix compiler warning about uninitialized inp_pos This should not have been reachable, but it warns on some compliers Branch: GraniteMoEShared Signed-off-by: Gabe Goodhart <ghart@us.ibm.com> * fix: Consoladate GraniteMoEShared into GraniteMoE for conversion Branch: GraniteMoEShared Signed-off-by: Gabe Goodhart <ghart@us.ibm.com> * fix: Consolidate GraniteMoEShared into GraniteMoE on the c++ side Branch: GraniteMoEShared Signed-off-by: Gabe Goodhart <ghart@us.ibm.com> --------- Signed-off-by: Gabe Goodhart <ghart@us.ibm.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.