Is it possible to update the environment of a deployed hugging face model?

[tleyden]

I'm using the following code snippet to deploy a huggingface model to sagemaker, based on this blog post.

llm_image = get_huggingface_llm_image_uri(
  "huggingface",
  version="0.9.3"
)

instance_type = "ml.g5.12xlarge"
number_of_gpu = 4
health_check_timeout = 300

# Define Model and Endpoint configuration parameter
config = {
  'HF_MODEL_ID': "meta-llama/Llama-2-7b-chat-hf", # model_id from hf.co/models
  'SM_NUM_GPUS': json.dumps(number_of_gpu), # Number of GPU used per replica
  'MAX_INPUT_LENGTH': json.dumps(2048),  # Max length of input text
  'MAX_TOTAL_TOKENS': json.dumps(4096),  # Max length of the generation (including input text)
  'MAX_BATCH_TOTAL_TOKENS': json.dumps(8192),  # Limits the number of tokens that can be processed in parallel during the generation
  'HUGGING_FACE_HUB_TOKEN': os.environ.get('HUGGING_FACE_HUB_TOKEN', ""), # token to access private models
}

llm_model = HuggingFaceModel(
  role=role,
  image_uri=llm_image,
  env=config
)

llm = llm_model.deploy(
  initial_instance_count=1,
  instance_type=instance_type,
  container_startup_health_check_timeout=health_check_timeout, # 10 minutes to be able to load the model
)

This is working and I am able to do inference on the endpoint that is created.

Is there a way to update the HF_MODEL_ID environment variable from meta-llama/Llama-2-7b-chat-hf to meta-llama/Llama-2-13b-chat-hf? And if that is possible, would changing that cause the endpoint to switch to using the 13b model?

I checked the hugging face + sagemaker docs but don't see any way to update the model. Any help would be most appreciated!