王金旭
9cd719af21
* dspark: support speculators-format checkpoints (SpecForge exports) Speculators-format DSpark drafts (e.g. SpecForge exports for the Gemma-4-26B-A4B target) differ from the dense DeepSpec checkpoints in three ways: - the config nests the backbone hparams under transformer_layer_config and gives the extract layers as aux_hidden_state_layer_ids - the block is the DFlash 1+N fill-in layout: the anchor slot is a bonus token, not a prediction slot. Written as dflash.bonus_anchor; such drafts build the block and read the mask positions exactly like DFlash (n_max drafts from a 1+n_max block), only the Markov/confidence sampling comes from DSpark - the draft output vocab may be reduced (draft_vocab_size < vocab_size) with a d2t remap table. The converter expands lm_head/markov_w2 back to the full vocab and synthesizes an lm_head bias of -1e9 on the rows the draft cannot produce, so the runtime needs no d2t remapping. Such drafts ship their own (now optional) token_embd/output tensors instead of sharing the target's Verified against gemma4-26b-a4b-dspark: greedy outputs are byte-identical with and without the draft; acceptance 0.46, mean draft len 3.7 (n_max 6). Co-authored-by: desovo7 <942845546@qq.com> Assisted-by: Claude Fable 5 * dspark: fold the speculators draft class into DSparkModel One class now covers every DSpark variant. What used to pick the class is a single flag, because the arch name turns out to be the only thing that separates the two families: SpecForge also exports a flat schema that carries no speculators_* fields yet still uses the 1+N bonus-anchor block, so keying on those fields would silently mis-read its drafts. Also rename i0 to i_first_pred in the draft read loop and the Markov head, and give the head a real bonus_anchor bool instead of testing i0 > 0. Converting the Qwen3-8B DeepSpec draft and both gemma-4 speculators drafts produces byte-identical GGUFs. The one behaviour change is that the markov_head_type check now also covers the DeepSpec checkpoints, which previously skipped it. Co-authored-by: desovo7 <942845546@qq.com> Assisted-by: Claude Opus 5 * dspark: address review comments - rename bonus_anchor to sample_from_anchor (GGUF key and code), matching the checkpoint config field; absent key still means anchor-first - rework the reduced draft vocab to match EAGLE3: d2t is written as I64 absolute target ids and the logits are scattered at runtime, instead of expanding lm_head/markov_w2 and synthesizing an output bias at conversion - move the t2d skip to modify_tensors, like EAGLE3 - drop _is_specforge: the arch name only picks the sample_from_anchor default, embed/lm_head sharing is decided by the draft vocab size - deduplicate the tok_embd create_tensor left behind by the rebase Verified with the RedHat gemma-4-31b speculator draft: greedy output is byte-identical with and without the draft; acceptance 0.26 (n_max 7). Co-authored-by: desovo7 <942845546@qq.com> Assisted-by: Claude Fable 5 * dspark: fold the sample_from_anchor read into the block_size block * dspark: fix flake8 continuation indent * clean up * dspark: key the sample_from_anchor default off the export format Co-authored-by: desovo7 <942845546@qq.com> Assisted-by: Claude Fable * dspark: drop t2d in filter_tensors Co-authored-by: desovo7 <942845546@qq.com> Assisted-by: Claude Fable * dspark: map model.lm_head instead of bypassing the dflash prefix Co-authored-by: desovo7 <942845546@qq.com> Assisted-by: Claude Fable --------- Co-authored-by: desovo7 <942845546@qq.com> Co-authored-by: ruixiang63 <wangruixiang07@outlook.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.