You have an Azure Machine Learning workspace named WS1. You plan to use Azure Machine Learning SDK v2 to register a model as an asset in WS1 from an artifact generated by an MLflow run. The artifact…

t//model/ is an incomplete and incorrect syntax for referencing job outputs or model paths in Azure Machine Learning.

azureml://registries refers to model registries, not a specific artifact within a job run.

mlflow-model/ is part of the path within a job's output but is not a complete reference to a job artifact on its own. It needs the job and output context.

When referencing artifacts from a specific job's named output in Azure Machine Learning SDK v2, the azureml://jobs/<job_name>/outputs/<output_name>/ syntax is used. For MLflow models specifically, the convention is often to append mlflow-model/ to this path, making azureml://jobs/<job_name>/outputs/<output_name>/mlflow-model/ the correct way to reference the model artifact location for registration.