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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':'Qwen/Qwen2.5-Omni-7B',
	'HF_TASK':'any-to-any'
}

# 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
)