Update how-to-use-mlflow-cli-runs.md

Author: ssalgadodev

articles/machine-learning/how-to-use-mlflow-cli-runs.md

@@ -232,7 +232,7 @@ mlflow.autolog()
 
 ## Manage models
 
-Register and track your models with the [Azure Machine Learning model registry](concept-model-management-and-deployment.md#register-package-and-deploy-models-from-anywhere), which supports the MLflow model registry. Azure Machine Learning models are aligned with the MLflow model schema making it easy to export and import these models across different workflows. The MLflow-related metadata, such as job ID, is also tracked with the registered model for traceability. Users can submit training jobs, register, and deploy models produced from MLflow jobs.
+Register and track your models with the [Azure Machine Learning model registry](concept-model-management-and-deployment.md#register-package-and-deploy-models-from-anywhere), which supports the MLflow model registry. Azure Machine Learning models are aligned with the MLflow model schema making it easy to export and import these models across different workflows. The MLflow-related metadata, such as run ID, is also tracked with the registered model for traceability. Users can submit training jobs, register, and deploy models produced from MLflow runs.
 
 If you want to deploy and register your production ready model in one step, see [Deploy and register MLflow models](how-to-deploy-mlflow-models.md).