Model Registry on Gemini Enterprise Agent Platform is a central repository where you can manage the lifecycle of your ML models. From Model Registry, you have an overview of your models so you can better organize and track them. When you have a model version you would like to deploy, you can assign it to an endpoint directly from the registry, or using aliases, deploy models to an endpoint.
Model Registry supports custom models and all AutoML data types - tabular and image. From the model version details page you can deploy to an endpoint and view specific model details. Model Registry provides a straightforward and streamlined interface to manage and deploy your best models to production.
There are many valid workflows for working in Model Registry. Follow these guidelines to understand what you can do in Model Registry.
- Import models to Model Registry.
- Add other aliases or labels to help you manage and organize your models and model versions.
- Deploy your models to an endpoint for online inference.
- View your model details and view performance metrics from the model details page.
Search and discover models using Knowledge Catalog
Knowledge Catalog is a platform for storing, managing, and accessing your metadata. Knowledge Catalog provides a way to search for your Agent Platform models across projects and regions.
For more information, see About data catalog management in Knowledge Catalog.
What's next
To get started using Model Registry, see: