Qwen/Qwen1.5-72B-Chat

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. Models - Hugging Face

hub = {
‘HF_MODEL_ID’:‘Qwen/Qwen1.5-72B-Chat’,
‘HF_TASK’:‘text-generation’
}

create Hugging Face Model Class

huggingface_model = HuggingFaceModel(
transformers_version=‘4.26.0’,
pytorch_version=‘1.13.1’,
py_version=‘py39’,
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
)

predictor.predict({
“inputs”: "Can you please let us know more details about your ",
})

for this I am getting this error

ModelError: An error occurred (ModelError) when calling the InvokeEndpoint operation: Received client error (400) from primary with message "{
“code”: 400,
“type”: “InternalServerException”,
“message”: “\u0027qwen2\u0027”
}