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Chapter 4. Run predictions with an AutoML model

After you save a notebook from the AutoML leaderboard in OpenShift AI, run it in a workbench to load the trained model and run predictions on sample data.

Prerequisites

  • You have created an AutoML optimization run and saved a notebook from the leaderboard. For more information, see Evaluate AutoML results.
  • You have a running workbench in your OpenShift AI project.
  • You have the connection details for the S3-compatible object storage bucket configured for the AI Pipelines server in your project.

Procedure

  1. In the OpenShift AI dashboard, open your workbench.

  2. Add the S3-compatible object storage connection configured for the AI Pipelines server to the workbench:

    1. On the workbench edit page, scroll to the Connections section.
    2. Click Attach existing connections.
    3. Select the connection and click Attach.
    4. Click Update workbench.
  3. Upload the saved notebook to the workbench.

  4. Open the notebook and run all cells. The notebook loads the trained model from S3 and runs predictions on sample data.

    The final cells in the notebook display sample predictions from test inputs.

Verification

  • Verify that all cells in the notebook completed without errors.
  • Verify that the model returns predictions for test inputs.
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