If you are training models in an automated environment where it's inconvenient to run shell commands, such as Google's CloudML, you should look at the documentation on Running in Automated Environments. Sign up for a free account in your shell or go to our sign up page. Add a few lines to your script to log hyperparameters and metrics. Weights and Biases is framework agnostic, but if you are using a common ML framework, you may find framework-specific examples even easier for getting started. We've built framework-specific hooks to simplify the integration for Keras, TensorFlow, PyTorch, Fast.ai,

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