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 and externally sourced models (for example, from Hugging Face). It also shows Cortex Fine-tuned models, and in future releases, will include other model types that you can create in Snowflake, providing a unified view of available models.
To display the Models page, in the Snowsight navigation menu, select AI & ML, and then select Models. The resulting list contains all the models in the Snowflake Model Registry in all the databases and schemas that your current role has access to.
Note
If you do not see any models, make sure your role has the required privileges.
To open a model’s details page, select the corresponding row in the Models list. The details page displays key model information, including the model’s description, tags, and versions.
To edit the model description or delete the model, select the … button.
To open the version’s details page, select a model version. This page displays model version metadata, such as metrics, and a list of available methods that can be called from Python or SQL.
To view code that calls the model function, select the SQL or Python link next to it. You can copy this code snippet into a Snowsight SQL worksheet or a Python notebook.
To add or modify metadata or delete the model version, select the … button.
The Files tab contains a list of the model version’s underlying artifacts. You can download individual files from this page.
