Create and deploy models locally and remotely with Amazon SageMaker
Version your AI models. Create copies of models whenever you adjust weights or other parameters. Every model version remains operational and accessible.
Adjust weights and other parameters on your models
Add models to a project
Assign models for pre-labeling. Use a model to provide suggestions for human labelers to accept, adjust, or ignore in the labeling interface.
Directly predict using deployed models. Use prediction to debug your model or provide a direct labeled output.
Deploy and test models locally with new CLI tools
Updated
Enjoy more detailed SDK log outputs thanks to Rich library implementation
Automatically verify model responses to ensure compatibility with super.AI schema
Shorter build time for AI containers through staged builds using a source-to-image package
