I am using the given template code to make a SageMaker endpoint from my conversational HF model:
from sagemaker.huggingface import HuggingFaceModel
import sagemaker

role = sagemaker.get_execution_role()
# Hub Model configuration. https://huggingface.co/models
hub = {
	'HF_MODEL_ID':'rachelcorey/DialoGPT-medium-kramer',
	'HF_TASK':'conversational'
}

# create Hugging Face Model Class
huggingface_model = HuggingFaceModel(
        transformers_version='4.12',
        pytorch_version='1.9',
	py_version='py38',
	env={ 'HF_TASK':'conversational' },
	role=role, 
)

# deploy model to SageMaker Inference
predictor = huggingface_model.deploy(
	initial_instance_count=1, # number of instances
	instance_type='ml.t2.medium' # ec2 instance type
)

The code has been revised based on the answers from this thread: Deploying a conversational pipeline on AWS - #3 by philschmid which is doing exactly what I want to do. I’ve installed the proper versions of pytorch and transformers.
When I run the code, I get this error:
UnexpectedStatusException: Error hosting endpoint huggingface-pytorch-inference-2022-01-12-15-00-34-671: Failed. Reason:  The primary container for production variant AllTraffic did not pass the ping health check. Please check CloudWatch logs for this endpoint..

When I go into the logs, I see this message about 100000 times:
ERROR - Given model-path /opt/ml/model is not a valid directory. Point to a valid model-path directory.

And also this message a couple times, but I assume it’s related to the previous error:
subprocess.CalledProcessError: Command '['model-archiver', '--model-name', 'model', '--handler', 'sagemaker_huggingface_inference_toolkit.handler_service', '--model-path', '/opt/ml/model', '--export-path', '/.sagemaker/mms/models', '--archive-format', 'no-archive', '--f']' returned non-zero exit status 1.

I tried to create this directory in opt/ml/ before running the code but it has no effect on the issue it seems.
According to some research, this is the directory that SageMaker puts trained models… However, my model is on HF, not trained by SageMaker… should I put the model files in that directory? Not sure what to do here. Do I ask AWS support for help with this instead of posting here? Any help is much appreciated, thank you in advance!