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':'lmstudio-community/gemma-3n-E4B-it-MLX-8bit',
'HF_TASK':'image-text-to-text'
}

create Hugging Face Model Class

huggingface_model = HuggingFaceModel(
transformers_version='4.49.0',
pytorch_version='2.6.0',
py_version='py312',
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
)