sagemaker_code.py

!pip install transformers
!pip install -U sagemaker
import sagemaker
import boto3
from sagemaker.huggingface import HuggingFaceModel

try:
	role = sagemaker.get_execution_role()
except ValueError:
	iam = boto3.client('iam')
	role = iam.get_role(RoleName='sagemaker_execution_role')['Role']['Arn']

# Hub Model configuration. https://huggingface.co/models
hub = {
	'HF_MODEL_ID':'cardiffnlp/twitter-roberta-base-sentiment-latest',
	'HF_TASK':'text-classification'
}

# create Hugging Face Model Class
huggingface_model = HuggingFaceModel(
	transformers_version='4.37.0',
	pytorch_version='2.1.0',
	py_version='py310',
	env=hub,
	role=role, 
)

print("done")

# 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 battery life sucks",
})