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Version: 1.38


This article guides you through deploying one of our sample models: the Scikit-learn census example and making your first prediction. However, you can also follow the steps to deploy a model from a repository of your own.


Using Deeploy Cloud? The Scikit-learn census example is included in the 'Example' Workspace by default, so you can start at step 3.

  1. Navigate to an existing Workspace or create a new one
  2. Navigate to Repositories and click Add. Copy the HTTPS path from the Scikit-learn census example Git repository into the designated field and click Save.
    • If you're trying to add a different repository, consult add a Repository for more details.
  3. Navigate to Deployments and click Create.
  4. Choose the existing Repository option. Select the Repository, the master branch, and the latest commit
  5. Choose a name for your Deployment and optionally add a description. Other metadata can be adjusted in the 'metadata.json' file at the root of the folder you are deploying from (learn more about metadata).
  6. Select the scikit-learn model framework.
    • You can leave the options untouched
  7. Choose the trained explainer option and select the SHAP kernel explainer framework.
    • You can leave the options untouched
  8. Skip the transformer framework and compliance insights
  9. Click Deploy
  10. Wait until your Deployment has finished deploying. Click on the create deployment event to view more details.
  11. Navigate to the Test page (located at the Manage dropdown) to test your Deployment. If you added example input during step 5, click Use example input. Otherwise, copy and pate the example input from the example-request.json file in the Scikit-learn census example Git repository into the request field. Click Predict.
  12. View the details of your prediction by navigating to the Predictions page. Click Explain to view an explanation of the prediction.