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kmkurn/pytorch-crf has 978 GitHub stars and 154 forks. Star changes are not measured yet. Last checked 2026-11-14 13:22 UTC. Last push 2024-06-09.

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(Linear-chain) Conditional random field in PyTorch.

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README.md

Original

pytorch-crf

Conditional random field in PyTorch <http://pytorch.org/>_.

.. image:: https://img.shields.io/pypi/pyversions/pytorch-crf.svg?style=flat :target: https://img.shields.io/pypi/pyversions/pytorch-crf.svg?style=flat :alt: Python versions

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This package provides an implementation of linear-chain conditional random field <https://en.wikipedia.org/wiki/Conditional_random_field>_ (CRF) in PyTorch. This implementation borrows mostly from AllenNLP CRF module <https://github.com/allenai/allennlp/blob/master/allennlp/modules/conditional_ra ndom_field.py>_ with some modifications.

Documentation

https://pytorch-crf.readthedocs.io/

License

MIT

Contributing

Contributions are welcome! Please follow these instructions to install dependencies and running the tests and linter.

Installing dependencies

Make sure you setup a virtual environment with Python. Then, install all the dependencies in requirements.txt file and install this package in development mode.

::

pip install -r requirements.txt
pip install -e .

Setup pre-commit hook

Simply run::

ln -s ../../pre-commit.sh .git/hooks/pre-commit

Running tests

Run pytest in the project root directory.

Running linter

Run flake8 in the project root directory. This will also run mypy, thanks to flake8-mypy package.