Launch experiments from the UI, CLI or GitHub. Your code, container, and dataset are packaged and remotely executed.
During training, your experiment logs begin streaming and graphs are plotted in realtime. Once complete, the instance tears down automatically.
Compare your results, iterate quickly, and collaborate with others. Make your experiment public to share with others.
Seamlessly submit a hyperparameter sweep via the CLI and UI.
Train models from a git commit or branch and view results in GitHub.
Multi-node training and inference with zero setup or management.
Job scheduling, resource provisioning, cluster management, and more.
Powerful CLI and native Python integrations. Construct pipelines, train at scale, and track results.