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](../../../_images/model-registry-model-list.png)
Note
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](../../../_images/model-registry-model-details.png)
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](../../../_images/model-registry-model-version-details.png)
Click the … button to add or modify metadata or to delete the model version.