If your organization is using AI Factsheets as part of an AI governance strategy, you can track models after adding them to a space.

Tracking a model populates a factsheet in an associated model use case. The model use cases are maintained in a model inventory in a catalog, providing a way for all stakeholders to view the lifecyle details for a machine learning model. From the inventory, collaborators can view the details for a model as it moves through the model lifecycle, including the request, development, deployment, and evaluation of the model.

To enable model tracking by using AI Factsheets:

1. From the asset list in your space, click a model name and then click the Model details tab.
2. Click Track this model.
3. Associate the model with an existing model use case in the inventory or create a new use case.
4. Specify the details for the new use case, including specifying a catalog if you have access to more than one, and save to register the model. A link to the model inventory is added to the model details page.
5. Click the link to open the model use case in the inventory.
6. Optional: update the model use case. For example, add tags, supporting documentation, or other details.

Parent topic: Assets in deployment spaces