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Quickstart

Here is a quick example tutorial on how to run the ML backend with a simple text classifier:

  1. Clone repo

    git clone https://github.com/heartexlabs/label-studio-ml-backend  
  2. Setup environment

    cd label-studio-ml-backend
    pip install -e .
    cd label_studio_ml/examples
    pip install -r requirements.txt
  3. Create new ML backend

    label-studio-ml init my_ml_backend --script label_studio_ml/examples/simple_text_classifier.py
  4. Start ML backend server

    label-studio-ml start my_ml_backend
  5. Run Label Studio connecting it to the running ML backend from the project settings page

Create your own ML backend

Check examples in label_studio_ml/examples directory.

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Configs and boilerplates for Label Studio's Machine Learning backend

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  • Python 99.3%
  • Dockerfile 0.7%