koboldcpp/gguf-py
Sam ef0144c087
model: support GLM 4.5 family of models (#14939)
* model: Add GLM 4.5 (#14921)

Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com>

* Merge in PR suggestions

Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com>

* model: Add GLM 4.5 family of models (#14921)

1. Updated tensor_mapping.py with NextN tensor mappings

- Added proper tensor mappings for all NextN/MTP tensors in /Users/samm/git/llama.cpp/gguf-py/gguf/tensor_mapping.py
- Added mappings for: eh_proj, embed_tokens, enorm, hnorm, shared_head.head, shared_head.norm

2. Added num_nextn_predict_layers configuration

- Added LLM_KV_NUM_NEXTN_PREDICT_LAYERS constant to llama-arch.h and llama-arch.cpp
- Added num_nextn_predict_layers field to llama_hparams struct
- Updated GLM4_MOE parameter loading in llama-model.cpp to read this parameter
- Modified tensor loading logic to conditionally load NextN tensors based on num_nextn_predict_layers
- Added GGUF writer support in gguf_writer.py with add_num_nextn_predict_layers() method
- Updated conversion script to extract and write this parameter from HuggingFace config

3. Added FIM tokens for GLM4_MOE

- Added GLM-4.5's FIM tokens to llama-vocab.cpp:
  - <|code_prefix|> for FIM_PRE
  - <|code_suffix|> for FIM_SUF
  - <|code_middle|> for FIM_MID

4. Removed manual NextN tensor handling

- Removed the special-case handling in convert_hf_to_gguf.py that manually mapped NextN tensors
- NextN tensors are now handled automatically through the proper tensor mapping system

* glm 4.5 update tensors names

* model: glm 4.5 apply suggestions from code review

Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com>

* Update src/llama-model.cpp

Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com>

* model: glm 4.5 apply suggestions from code review

Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com>

* model: glm 4.5 apply suggestions from code review

* Apply suggestions from code review

* patch broken chat template

* typings fix

* add TENSOR_SKIP flag


Co-authored-by: Diego Devesa <slarengh@gmail.com>

* Update src/llama-model-loader.h

Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com>

---------

Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com>
Co-authored-by: Diego Devesa <slarengh@gmail.com>
2025-08-04 20:29:25 +02:00
..
examples Refactor gguf scripts to improve metadata handling (#11909) 2025-02-26 08:04:48 -05:00
gguf model: support GLM 4.5 family of models (#14939) 2025-08-04 20:29:25 +02:00
tests tts : add OuteTTS support (#10784) 2024-12-18 19:27:21 +02:00
LICENSE gguf : make gguf pip-installable 2023-08-25 09:26:05 +03:00
pyproject.toml gguf-py : make sentencepiece optional (#14200) 2025-06-19 15:56:12 +02:00
README.md gguf-py : GGUF Editor GUI - Python + Qt6 (#12930) 2025-04-18 20:30:41 +02:00

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

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.

  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.