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APPLIES TO: Azure CLI ml extension v2 (current)
The source JSON schema can be found at https://azuremlschemas.azureedge.net/latest/model.schema.json.
Note
The YAML syntax detailed in this document is based on the JSON schema for the latest version of the ML CLI v2 extension. This syntax is guaranteed only to work with the latest version of the ML CLI v2 extension. You can find the schemas for older extension versions at https://azuremlschemasprod.azureedge.net/.
Key | Type | Description | Allowed values |
---|---|---|---|
$schema |
string | The YAML schema. | |
name |
string | Required. Name of the model. | |
version |
int | Version of the model. If omitted, Azure Machine Learning will autogenerate a version. | |
description |
string | Description of the model. | |
tags |
object | Dictionary of tags for the model. | |
path |
string | Either a local path to the model file(s), or the URI of a cloud path to the model file(s). This can point to either a file or a directory. | |
type |
string | Storage format type of the model. Applicable for no-code deployment scenarios. | custom_model , mlflow_model , triton_model |
flavors |
object | Flavors of the model. Each model storage format type may have one or more supported flavors. Applicable for no-code deployment scenarios. |
The az ml model
command can be used for managing Azure Machine Learning models.
Examples are available in the examples GitHub repository. Several are shown below.
$schema: https://azuremlschemas.azureedge.net/latest/model.schema.json
name: local-file-example
path: mlflow-model/model.pkl
description: Model created from local file.
$schema: https://azuremlschemas.azureedge.net/latest/model.schema.json
name: local-mlflow-example
path: mlflow-model
type: mlflow_model
description: Model created from local MLflow model directory.
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