title: How to overcome TrainingException when training a large model with Azure Machine Learning service?
body: <p>I'm training a large-ish model, trying to use for the purpose <a href="https://docs.microsoft.com/en-us/azure/machine-learning/service/tutorial-train-models-with-aml#create-an-estimator" rel="nofollow noreferrer">Azure Machine Learning service</a> in Azure notebooks.</p>
  
  <p>I thus create an <code>Estimator</code> to train locally:</p>
  
  <pre><code>from azureml.train.estimator import Estimator
  
  estimator = Estimator(source_directory='./source_dir',
                        compute_target='local',
                        entry_script='train.py')
  </code></pre>
  
  <p>(my <code>train.py</code> should load and train starting from a large word vector file).</p>
  
  <p>When running with </p>
  
  <pre><code>run = experiment.submit(config=estimator)
  </code></pre>
  
  <p>I get </p>
  
  <blockquote>
    <p>TrainingException: </p>
    
    <p>====================================================================</p>
    
    <p>While attempting to take snapshot of
    /data/home/username/notebooks/source_dir Your total
    snapshot size exceeds the limit of 300.0 MB. Please see
    <a href="http://aka.ms/aml-largefiles" rel="nofollow noreferrer">http://aka.ms/aml-largefiles</a> on how to work with large files.</p>
    
    <p>====================================================================</p>
  </blockquote>
  
  <p>The link provided in the error is likely <a href="https://github.com/MicrosoftDocs/azure-docs/issues/26076" rel="nofollow noreferrer">broken</a>. 
  Contents in my <code>./source_dir</code> indeed exceed 300 MB.<br>
  How can I solve this?</p>