Model Registry Collections - Amazon SageMaker

Model Registry Collections

You can use Collections to group registered models that are related to each other and organize them in hierarchies to improve model discoverability at scale. With Collections, you can organize registered models that are associated with one another. For example, you could categorize your models based on the domain of the problem they solve as Collections titled NLP-models, CV-models, or Speech-recognition-models. To organize your registered models in a tree structure, you can nest Collections within each other. Any operations you perform on a Collection, such as create, read, update, or delete, will not alter your registered models. You can use the Amazon SageMaker Studio UI or the Python SDK to manage your Collections.

The Collections tab in the Model Registry displays a list of all the Collections in your account. The following sections describe how you can use options in the Collections tab to do the following:

  • Create Collections

  • Add Model Groups to a Collection

  • Move Model Groups between Collections

  • Remove Model Groups or Collections from other Collections

Any operation you perform on your Collections does not affect the integrity of the individual Model Groups they contain—the underlying Model Group artifacts in Amazon S3 and Amazon ECR are not modified.

While Collections provide greater flexibility in organizing your models, the internal representation imposes some constraints on the size of your hierarchy. For a summary of these constraints, see Constraints.

The following topics show you how to create and work with Collections in the Model Registry.