Machine Learning Backends

You can easily connect your favorite machine learning framework with Heartex Machine Learning (ML) SDK or Label Studio ML toolkit. That gives you the opportunities to use:

Connecting ML backend

Connecting Machine Learning backend could be done in 2 steps:

  1. Create and launch Heartex/Label Studio-compatible Machine Learning (ML) server according to
  2. Go to Project Settings page, then switch to the Machine Learning tab and click on Add Custom Model. You will be prompted to enter ML backend title and URL.



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

  1. Clone repo
    git clone
  1. Setup environment
    cd label-studio
    pip install -e .
    cd label_studio/ml/examples
    pip install -r requirements.txt
  1. Create new ML backend
    label-studio-ml init my_ml_backend --script label_studio/ml/examples/
  1. Start ML backend server
    label-studio-ml start my_ml_backend