SDK release

New

• 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