There is a command group 'az_ml_model'. This group of commands could 'manage azure ml models'. The group of commands has global parameter '--debug' which means 'Increase logging verbosity to show all debug logs.'. The group of commands has global parameter '--help -h' which means 'Show this help message and exit.'. The group of commands has global parameter '--only-show-errors' which means 'Only show errors, suppressing warnings.'. The group of commands has global parameter '--output -o' which means 'Output format.'. The group of commands has global parameter '--query' which means 'JMESPath query string. See <a href="http://jmespath.org/">http://jmespath.org/</a> for more information and examples.'. The group of commands has global parameter '--subscription' which means 'Name or ID of subscription. You can configure the default subscription using `az account set -s NAME_OR_ID`.'. The group of commands has global parameter '--verbose' which means 'Increase logging verbosity. Use --debug for full debug logs.'. This group contains a child command 'az_ml_model_create'.The syntax is: az ml model create [--datastore]
                   [--description]
                   [--file]
                   [--name]
                   [--no-wait]
                   [--path]
                   [--registry-name]
                   [--resource-group]
                   [--set]
                   [--stage]
                   [--tags]
                   [--type]
                   [--version]
                   [--workspace-name]. The 1th example of the child command would be to use it to 'create a model from a yaml specification file', the syntax is: az ml model create --file model.yml --resource-group my-resource-group --workspace-name my-workspace. The 2th example of the child command would be to use it to 'create a model from a local folder using command options', the syntax is: az ml model create --name my-model --version 1 --path ./my-model --resource-group my-resource-group --workspace-name my-workspace. The 3th example of the child command would be to use it to 'create a model using mlflow run uri format  runs   run id   path to model relative to the root of the artifact location   and command options', the syntax is: az ml model create --name my-model --version 1 --path runs:/c42d2507-4953-4a7c-a4c1-2b5bfe0ac64e/model/ --type mlflow_model --resource-group my-resource-group --workspace-name my-workspace. The 4th example of the child command would be to use it to 'create a model from a named job output using azureml job uri format  azureml   jobs  job name  outputs  named output  paths  path to model relative to the named output location   and command options  the default named output is artifacts', the syntax is: az ml model create --name my-model --version 1 --path azureml://jobs/c42d2507-4953-4a7c-a4c1-2b5bfe0ac64e/outputs/artifacts/paths/model/ --resource-group my-resource-group --workspace-name my-workspace. The 5th example of the child command would be to use it to 'create a model from a datastore  azureml   datastores  datastore name  paths  path to model relative to the root of the datastore location   using command options', the syntax is: az ml model create --name my-model --version 1 --path azureml://datastores/myblobstore/paths/models/cifar10/cifar.pt --resource-group my-resource-group --workspace-name my-workspace. The parameter '--datastore' is optional. the datastore to upload the local artifact to.. The parameter '--description' is optional. description of the model.. The parameter '--file -f' is optional. local path to the yaml file containing the azure ml model specification. the yaml reference docs for model can be found at: https://aka.ms/ml-cli-v2-model-yaml-reference.. The parameter '--name -n' is optional. name of the model.. The parameter '--no-wait' is optional. do not wait for the long-running operation to finish.. The parameter '--path -p' is optional. path to the model file(s). this can be either a local or a remote location. if specified, --name/-n and --version/-v must also be provided.. The parameter '--registry-name' is optional. if provided, the command will target the registry instead of a workspace. hence resource group and workspace won't be required.. The parameter '--resource-group -g' is optional. name of resource group. you can configure the default group using `az configure --defaults group=<name>`.. The parameter '--set' is optional. update an object by specifying a property path and value to set. example: --set property1.property2=<value>.. The parameter '--stage -s' is optional. stage of the model.. The parameter '--tags' is optional. space-separated key-value pairs for the tags of the object.. The parameter '--type -t' is optional. type of the model, allowed values are custom_model, mlflow_model and triton_model. the default type is custom_model.. The parameter '--version -v' is optional. version of the model.. The parameter '--workspace-name -w' is optional. name of the azure ml workspace. you can configure the default workspace using `az configure --defaults workspace=<name>`.. 