Overview

If you’ve already trained and converted your own model for mobile, you can use the custom model library in order to manage your models on the edge.

By using the custom model library, you’ll be able to monitor your model’s usage and performance and update your models over-the-air.

Supported Mobile ML Frameworks

Currently we support the following mobile machine learning frameworks:

Managing a Custom Model

Note

If you haven’t set up the SDK yet, make sure to go through those directions first. You’ll need to add the Core library to the app before using the specific feature or custom model libraries.

  1. In your project, create your custom model by uploading your model in one of the supported formats.

  2. After you’ve uploaded the model, you’ll want to take note of 2 things (Both of these can be found in the model details page):

    • Your API key which is generated as part of setting up the SDK.
    • Your model id which is used to track the specific model.
  3. Finally, you’ll need to add the specific library for the ML framework you’re using on mobile.