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import json import sagemaker import boto3 from sagemaker.huggingface import HuggingFaceModel, get_huggingface_llm_image_uri

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':'mistralai/Mixtral-8x7B-Instruct-v0.1', 'SM_NUM_GPUS': json.dumps(8) }

create Hugging Face Model Class

huggingface_model = HuggingFaceModel( image_uri=get_huggingface_llm_image_uri("huggingface",version="1.1.0"), env=hub, role=role, )

deploy model to SageMaker Inference

predictor = huggingface_model.deploy( initial_instance_count=1, instance_type="ml.g5.48xlarge", container_startup_health_check_timeout=300, )

send request

predictor.predict({ "inputs": "Digital Deviance Detective", })

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