readme: from sagemaker.huggingface import HuggingFaceModel
  import boto3
  
  iam_client = boto3.client('iam')
  role = iam_client.get_role(RoleName='{IAM_ROLE_WITH_SAGEMAKER_PERMISSIONS}')['Role']['Arn']
  # Hub Model configuration. https://huggingface.co/models
  hub = {
  	'HF_MODEL_ID':'bigscience/T0pp',
  	'HF_TASK':'text2text-generation'
  }
  
  # create Hugging Face Model Class
  huggingface_model = HuggingFaceModel(
  	transformers_version='4.6.1',
  	pytorch_version='1.7.1',
  	py_version='py36',
  	env=hub,
  	role=role, 
  )
  
  # deploy model to SageMaker Inference
  predictor = huggingface_model.deploy(
  	initial_instance_count=1, # number of instances
  	instance_type='ml.m5.xlarge' # ec2 instance type
  )
  
  predictor.predict({
  	'inputs': "The answer to the universe is"
  })