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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 )