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Conditional random field in PyTorch

Project description

pytorch-crf

Conditional random field in PyTorch.

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This package provides an implementation of conditional random field (CRF) in PyTorch. This implementation borrows mostly from AllenNLP CRF module with some modifications.

Requirements

  • Python 3.6

  • PyTorch 1.0.0

Installation

Install with pip:

$ pip install pytorch-crf

Or, install from Github for the latest version:

$ pip install git+https://github.com/kmkurn/pytorch-crf#egg=pytorch_crf

Documentation

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

License

MIT

Contributing

Contributions are welcome! Please follow these instructions to install dependencies and running the tests and linter. Make a pull request to develop branch once your contribution is ready.

Installing dependencies

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 .

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.

Project details


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