Snowflake Model Registry User Interface

The Models page in Snowsight allows you to find and explore machine learning models that you can use in Snowflake.

The Models page displays user-created models logged in the Snowflake Model Registry, including models developed with Snowpark ML as well as externally-sourced models (for example, from Hugging Face). In future releases, this page will include other model types that you can create in Snowflake, providing a unified view of available models.

To display the Models page, select AI & ML in the Snowsight navigation menu, then select Models. The resulting list contains all models in the Snowflake Model Registry in all databases and schemas that your current role has access to.

The Models page, displaying a list of the available machine learning models


If you do not see any models, make sure your role has the required privileges.

To open a model’s details page, click the corresponding row in the Models list. The details page, shown here, display key model information including the model’s description, tags, and versions.

A model details page, displaying key model information

Click the button to edit the model description or to delete the model.

Click a model version to open the version’s details page, shown below. This page displays model version metadata, such as metrics, and a list of available methods that can be called from Python or SQL.

A model version details page, displaying information about the model version

Click the button to add or modify metadata or to delete the model version.