deploy.py

from sagemaker.huggingface import HuggingFaceModel
import sagemaker

role = sagemaker.get_execution_role()
hub = {	'HF_MODEL_ID':'bigscience/T0_3B','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(1,'ml.g4dn.2xlarge')
# run inference
predictor.predict({
	'inputs': "Is this review positive or negative? Review: Best cast iron skillet you will every buy."
})
# [{'generated_text': 'Positive'}]

predictor.predict({
	'inputs': "A is the son's of B's uncle. What is the family relationship between A and B?"
})
# [{'generated_text': "B is A's cousin."}]