models.install
- 11 Nov 2020
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models.install
- Updated on 11 Nov 2020
- 1 Minute to read
- Contributors
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- DarkLight
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Description
Initiates an asynchronous installation of a specified machine learning (ML) model from your app's locker.
When installation completes, the model is stored inside the runtime's cache object using a provided key.
The Ux.ResourceReady event is triggered so you can take action when your model becomes available.
Input Parameters
| Name | Type | Required | Description |
|---|---|---|---|
| token | Text | Yes | Model's locker token |
| key | Text | Yes | Unique cache key where model will be stored |
Returns
No return value.
Examples
// inside the Ux.Initialize script...
// install model from app's locker using its token
ai.models.install("TOKEN", "riskModel");
Model Formats
The following model formats are supported:
| Name | Description |
|---|---|
| javascript | Javascript model format |
| bayesialab | Bayesialab model format |
| tf * | Tensor Flow model format |
| onnx * | Open ONNX AI CNN format |
Formats with an asterisk coming soon
Remarks
Use this function to install a previously trained machine learning (ML) model that you would like to use while your app is running.
One common scenario is to install a model during intialization. Next, as a user interacts with your app in realtime, gather their inputs (using the Ux.Change event) and run them through your model. Finally, display model results inside the attached insights panel or adjust your app's language output.
Two-Step Process
Installing models can be slow based on connection speeds and the size of the models being downloaded.
As a result, downloading models requires a two-step process. First, you must initiate the installation from one script (typically Ux.Initialize). Second, you run the model (using ai.models.run) after the installation completes from another script (typically Ux.ResourceReady or Ux.Change).
By separating these steps, the user's experience remains fluid. Otherwise, the user interface would freeze until the installation completes, resulting in a poor user experience.