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Verta MLflow Integration
Verta Model Catalog helps you create a unified model inventory, regardless of where the model was originally built or trained. To simplify the process of importing models into Verta Model Catalog, we have developed a Verta MLflow integration that allows you to batch import MLflow models with just a few clicks.
This feature is in ALPHA meaning we would love for you to try it but caution that it may sometimes behave oddly. Please provide any feedback you have to [email protected] and keep an eye out for an email from our product team after using this feature.
Click on the “Import Models” button in the Model Catalog homepage.
Pick MLflow as the source for import
Provide your MLflow credentials to connect and fetch the models. The credentials required are;
- DATABRICKS_TOKEN (Your API Key)
After successful authentication, your MLflow model list will be visible in the UI
- You can manually select the models you wish to import from the UI list view
- You can also use advanced filtering capabilities to select a subset of models. Filtering options include model name, tag, or creation date range
Verify the model selection/filtering is as expected and then long press the import button to start the batch import job
Please note that the system will not import a model if
- It has a duplicated name
- It has no version
- In the case that the version has an error
- If the version has no artifacts, or it's not compatible with the Verta system
- If Verta cannot map the model stages correctly
- After initiating the batch import job, you'll be redirected to the model import status page to track progress
- In this view, you can track the import status of the models, including any errors or failures
- You can access the import status page at any time from the 'Import Model' button
- Once the import is complete, you can access the models and their associated artifacts in Verta Model Catalog
- The models will be automatically tagged as 'mlflow_import,' making it easy for you to search and filter them