docstr: In this initialize function, the HF large model is loaded and
  partitioned using DeepSpeed.
  Args:
      ctx (context): It is a JSON Object containing information
      pertaining to the model artifacts parameters.
docstr_tok: ["In","this","initialize","function",",","the","HF","large","model","is","loaded","and","partitioned","using","DeepSpeed",".","Args",":","ctx","(","context",")",":","It","is","a","JSON","Object","containing","information","pertaining","to","the","model","artifacts","parameters","."]
code: def initialize(self, ctx):
      """In this initialize function, the HF large model is loaded and
      partitioned using DeepSpeed.
      Args:
          ctx (context): It is a JSON Object containing information
          pertaining to the model artifacts parameters.
      """
      logger.info("Start initialize")
      model_name = ctx.model_yaml_config["handler"]["model_name"]
      model_path = ctx.model_yaml_config["handler"]["model_path"]
      if not os.path.exists(model_path):
          model_path = os.environ["LLAMA2_Q4_MODEL"]
      seed = int(ctx.model_yaml_config["handler"]["manual_seed"])
      torch.manual_seed(seed)
  
      self.model = Llama(model_path=model_path)
  
file_path: serve/examples/LLM/llama2/chat_app/llama_cpp_handler.py
imports: import logging
  import os
  from abc import ABC
  import torch
  from llama_cpp import Llama
  from ts.torch_handler.base_handler import BaseHandler
label_desc: Use image node_id 2 for calling the LlamaCppHandler obj's underlying member method code with example usage: obj.initialize(ctx) without return types