Preparing a model for deployment

After you train a model, you can deploy it by using the OpenShift AI model serving capabilities.

To prepare a model for deployment, you must move the model from your workbench to your S3-compatible object storage. You use the data connection that you created in the Storing data with data connections section and upload the model from a notebook. You also convert the model to the portable ONNX format. ONNX allows you to transfer models between frameworks with minimal preparation and without the need for rewriting the models.

Prerequisites

  • You created the data connection My Storage.

    Workbench data connection form

  • You added the My Storage data connection to your workbench.

    Data storage in workbench
Procedure

  1. In your Jupyter environment, open the 2_save_model.ipynb file.

  2. Follow the instructions in the notebook to make the model accessible in storage and save it in the portable ONNX format.

Verification

When you have completed the notebook instructions, the models/fraud/1/model.onnx file is in your object storage and it is ready for your model server to use.

Next step

Deploying a model