Conditional random field in PyTorch <http://pytorch.org/>_.
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This package provides an implementation of 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.
https://pytorch-crf.readthedocs.io/
MIT
Contributions are welcome! Please follow these instructions to install dependencies and running the tests and linter.
Make sure you setup a virtual environment with Python and PyTorch
installed. Then, install all the dependencies in requirements.txt file and
install this package in development mode.
::
pip install -r requirements.txt
pip install -e .
Simply run::
ln -s ../../pre-commit.sh .git/hooks/pre-commit
Run pytest in the project root directory.
Run flake8 in the project root directory. This will also run mypy,
thanks to flake8-mypy package.
FAQs
Conditional random field in PyTorch
We found that pytorch-crf demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 1 open source maintainer collaborating on the project.
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