ML as Code

The ML as Code option generates editable source code for the trained model, making it easier to review, customize, and integrate into existing systems or workflows. This method is ideal for MLOps teams who want to version-control and manage the model as part of their software pipeline.

To use this option, provide the UsecaseID and Version, then click Generate.

You can either download the generated code locally or upload it directly to a GitHub repository. This enables flexible, code-first model deployment in environments without AION.