REST API Reference

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Registering a machine learning model

Use the Documents resource to register a machine learning model after you upload the model file.

To register a machine learning model, include the project or folder ID in the URI. Use the following URI:

/frs/v1/Projects('<project ID>')/Documents

Include the following fields in the request:

Field	Type	Description
name	String	Machine learning model asset name.
description	String	Optional. Description of the machine learning model.
documentType	String	Use MLOPS_MODEL .
nativeData	Object	Blob object that defines the machine learning model.

Include the following fields in the nativeData object:

Field	Type	Description
name	String	Machine learning model asset name.
framework	String	Framework used to create the machine learning model. Use one of the following values: Python PyTorch TensorFlow
framework_type	String	Internal type of the framework. For a Python model, use Custom . For a PyTorch or TensorFlow model, use Standard .
file_id	String	Model file ID generated when you upload the model file.
file_name	String	Name of the model file. The name must match the file name you used to generate the model file ID.
size	String	Size of the model file in GB.
file_type	String	Use zip .
inputField		Input fields that the machine learning model expects. Include at least one input field.
name	String	Name of the field.
dataType	String	Data type of the field.
shape	String	Required for array data types. Shape of the array. For example, [2,3] .
outputField		Output fields that the machine learning model returns. Include at least one output field.
name	String	Name of the field.
dataType	String	Data type of the field.
shape	String	Required for array data types. Shape of the array. For example, [2,3] .