After creating one or more datasets through the CLI or the Python API, the model CLI can be used for model training. With the model CLI a range of scikit-learn models and a PyTorch fully-connected neural net can be trained. The model CLI provides the same main training steps as the Python API, namely hyperparameter optimization, cross-validation and test set predictions. Finally, after model training has completed, the trained models can be used to make predictions on new sets of molecules with the predict CLI.