Modelerror when deploying openchat3.5
Hi all,I am deployingopenchat3.5model on sagemaker. first I uploaded all the files into the S3 storage and manged access and deployed the model successfully. I am getting error when trying to ask questions with it. Anybody knows how to use “predict” or “invoke_endpoint” with my given model?below is the code which describes the functionality and error:hub2 = {‘HF_TASK’: ‘text-generation’,}model_path = “s3://penchatbotmodel/model.tar.gz”huggingface_model2 = HuggingFaceModel(role=role,env=hub2,py_version=‘py36’,transformers_version=‘4.6.1’,pytorch_version=‘1.7.1’,model_data=model_path,)predictor = huggingface_model2.deploy(initial_instance_count=1,instance_type=“ml.g5.2xlarge”,endpoint_name=“ChatBotPoint2”,)prompt=“”“<|prompter|>How can i stay more active during winter? Give me 3 tips.<|endoftext|><|assistant|>”“”hyperparameters for llmpayload = {“inputs”: prompt,“parameters”: {“do_sample”: True,“top_p”: 0.7,“temperature”: 0.7,“top_k”: 50,“max_new_tokens”: 256,# “repetition_penalty”: 1.03,# “stop”: [“<|endoftext|>”]}}predictor.predict(payload )The Error:[ModelError  :](ModelError: An error occurred (ModelError) when calling the InvokeEndpoint operation: Received client error (400) from primary with message "{“code”: 400,“type”: “InternalServerException”,“message”: “\u0027mistral\u0027”})