Hi,
I'm trying to deploy an endpoint for of this model using sagemaker, specifically the code offered under 'Deploy':

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':'microsoft/BioGPT-Large-PubMedQA',
'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 ",
})

The deployment succeeded, but when calling predict, the workers die because they cannot load the model. When looking at the Cloudwatch logs, I see the following error:

2023-07-25T14:48:59,331 [INFO ] W-9000-microsoft__BioGPT-Large-P-stdout com.amazonaws.ml.mms.wlm.WorkerLifeCycle - ValueError: Could not load model /.sagemaker/mms/models/microsoft__BioGPT-Large-PubMedQA with any of the following classes: (<class 'transformers.models.auto.modeling_auto.AutoModelForCausalLM'>, <class 'transformers.models.biogpt.modeling_biogpt.BioGptForCausalLM'>).

Any idea on how to solve? Perhaps I need to use a newer version of transformers?