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articles/machine-learning/reference-azure-machine-learning-cli.md

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@@ -149,7 +149,7 @@ The following commands demonstrate how to use the CLI to manage resources used b
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> If you have a Python script that creates a run configuration object programmatically, you can use [RunConfig.save()](https://docs.microsoft.com/python/api/azureml-core/azureml.core.runconfiguration?view=azure-ml-py#save-path-none--name-none--separate-environment-yaml-false-) to save it as a runconfig file.
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> The full runconfig schema can be found in this [JSON file](https://github.com/microsoft/MLOps/blob/b4bdcf8c369d188e83f40be8b748b49821f71cf2/infra-as-code/runconfigschema.json).
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> The full runconfig schema can be found in this [JSON file](https://github.com/microsoft/MLOps/blob/b4bdcf8c369d188e83f40be8b748b49821f71cf2/infra-as-code/runconfigschema.json). The schema is self-documenting through the `description` key of each object. Additionally, there are enums for possible values, and a template snippet at the end.
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For more information, see [az ml run submit-script](https://docs.microsoft.com/cli/azure/ext/azure-cli-ml/ml/run?view=azure-cli-latest#ext-azure-cli-ml-az-ml-run-submit-script).
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