Added pip install above load model code.

Author: lobrien

articles/machine-learning/how-to-use-automlstep-in-pipelines.md

@@ -440,7 +440,11 @@ df = pd.DataFrame(deserialized_metrics_output)
 
 The code snippet above shows the metrics file being loaded from it's location on the Azure datastore. You can also load it from the downloaded file, as shown in the comment. Once you've deserialized it and converted it to a Pandas DataFrame, you can see detailed metrics for each of the iterations of the automated ML step.
 
-The model file can be deserialized into a `Model` object that you can use for inferencing, further metrics analysis, and so forth.
+The model file can be deserialized into a `Model` object that you can use for inferencing, further metrics analysis, and so forth. To load a `Model` locally, you'll need to have installed the Azure ML SDK.
+
+```azurepowershell
+pip install azureml-sdk[automl,explain]
+```
 
 ```python
 import pickle