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Easily deploy your machine learning model as an API endpoint in a few simple steps. Stop worrying about Kubernetes, Docker, and framework headaches.
Select an existing model or upload a new model from the interface or CLI.
Choose from your preferred runtime eg TensorFlow Serving, Flask, etc.
Set instance, types, autoscaling behavior, and other parameters. Click deploy!
Go from signup to training a model in seconds. Leverage pre-configured templates & sample projects.
Job scheduling, resource provisioning, cluster management, and more without ever managing servers.
Scale up training with a full range of GPU options with no runtime limits.
Automatic versioning, tagging, and life-cycle management. Develop models and compare performance over time.
Improve visibility into team performance. Invite collaborators or leverage public projects.
Get started with a library of sample projects you can clone and run in your own account.