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Chapter 5. Deploy an AutoML model for inference

After you register a model from the AutoML leaderboard, you can deploy it for inference with the AutoGluon serving runtime. Deploying the model creates a REST API endpoint that you can use to send prediction requests.

Prerequisites

  • You have registered a model from the AutoML leaderboard to a model registry. For more information, see Evaluate AutoML results.

  • The AutoGluon serving runtime is available in your project.

    Note

    An administrator can control the availability of serving runtimes for a project by managing ServingRuntime template resources. If the AutoGluon runtime has been disabled for your project, it does not appear as a selectable option in the deployment UI.

Procedure

  1. Deploy the registered model version from the model registry by following the steps in Deploying a model version from a model registry.

    Configure the deployment with the following values:

    • For Model framework, select autogluon - 1.
    • For Serving runtime, select AutoGluon ServingRuntime for KServe.

Verification

  • On the Deployments page, verify that the model deployment shows a status of Ready.
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