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Python library for the code serializer

Project description

spaCy powered Label Studio ML backend

spaCy integration for Label Studio. this is running besides the azure functions.

Demo video

running the backend

  1. prepare environment
python -m venv .venv
source venv/bin/activate
pip install -r requirements.txt
pip install --upgrade pip

Compile your library

python setup.py sdist bdist_wheel

Upload to Pypi

twine upload dist/* 

running tests

pytest tests/ -W ignore::DeprecationWarning
  1. start label studio
label-studio
  1. Start the backend and add the URL to your Label Studio project settings.
label-studio-ml start channel_ml_ner
  1. As you train new models, they will appear in a checkpoints directory. The latest checkpoint will be symlinked to latest-model.

modifying the config

In the channel_ml_ner directory, add your spaCy config.cfg file. You can optionally add a model-best folder from a pre-trained model, to get started with predictions straight away.

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