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.
running the backend
- prepare environment
python -m venv .venv
source .venv/bin/activate
pip install -r requirements-dev.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
- start label studio
label-studio
- Start the backend and add the URL to your Label Studio project settings.
label-studio-ml start channel_ml_ner
- As you train new models, they will appear in a
checkpoints
directory. The latest checkpoint will be symlinked tolatest-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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