mlinter
A standalone linter for Hugging Face Transformers model
integration files — modeling_*.py, modular_*.py, configuration_*.py, processing_*.py,
image_processing_*.py, video_processing_*.py, feature_extraction_*.py,
tokenization_*.py and generation_*.py under src/transformers/models/, plus test_tokenization_*.py under
tests/models/. It enforces the
structural conventions that keep hundreds of model implementations consistent with each other.
📖 Documentation: https://huggingface.github.io/transformers-mlinter/
The docs site is generated from mlinter/rules.toml, so its
rule reference is always in step with the
installed rules.
Installation
pip install transformers-mlinter
When working on the transformers repo, mlinter is included in the quality extras:
pip install -e ".[quality]"
Quick start
Run from the root of a transformers checkout:
mlinter # check every model integration file
mlinter --changed-only --base-ref origin/main # only what you changed
mlinter --list-rules # list rules and their default state
mlinter --rule TRF001 # explain one rule
Pass a path to check code that lives outside a transformers checkout — a model repository shipped on
the Hub with trust_remote_code, for instance, which has to honour the same conventions:
mlinter ~/models/LLaDA-8B-Instruct # a directory, searched recursively
mlinter path/to/modeling_llada.py # or a single file
See the CLI reference for every flag, the Python API, and cache locations.
Documentation map
| Page | What's there |
|---|---|
| Home | What mlinter checks and why, installation, how rule registration works |
| Rules | All rules, filterable, one page each with examples and exemptions |
| CLI usage | Every flag, output formats, cache, Python API |
| Suppressing rules | # trf-ignore, whole-file directives, cutoff dates, allowlists |
| Contributing a rule | Adding a rule, the add-mlinter-rule skill, constraints on a rule |
| Releasing | The tag-driven release process |
Development
git clone https://github.com/huggingface/transformers-mlinter
cd transformers-mlinter
pip install -e ".[dev]"
make test # pytest under tests/
make lint # ruff check + format --check
make format # auto-fix style
make typecheck # ty on mlinter/
Building the docs site
The rule pages are generated and git-ignored. Building needs the Ruby toolchain once:
cd docs && bundle install && cd ..
make docs # regenerate rule pages, build the site, check internal links
make docs-serve # live preview on http://localhost:4000/transformers-mlinter/
License
Apache-2.0. See LICENSE.
Release files for transformers-mlinter 0.1.5
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| transformers_mlinter-0.1.5.tar.gz | 137.4 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| transformers_mlinter-0.1.5-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 286.9 kB
Release files / transformers_mlinter-0.1.5.tar.gz
| Download URL | transformers_mlinter-0.1.5.tar.gz |
|---|---|
| Size | 137.4 kB |
| Tags | Source |
|
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| Tags | Python 3 |
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Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/7.0.0 CPython/3.13.14
|
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Aug 28, 2026.
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