code: def load(model_name_or_path):
      print(f"Loading model from {model_name_or_path} ...")
      # however, tensor parallel for running falcon will occur bugs
      tokenizer = AutoTokenizer.from_pretrained(
          model_name_or_path,
          trust_remote_code=True,
      )
      model = AutoModelForCausalLM.from_pretrained(
          model_name_or_path,
          device_map="auto",
          torch_dtype=torch.float16,
          trust_remote_code=True,
      )
      if tokenizer.pad_token_id is None:
          if tokenizer.eos_token_id is not None:
              tokenizer.pad_token_id = tokenizer.eos_token_id
          else:
              tokenizer.pad_token_id = 0
  
      model.eval()
  
      return model, tokenizer
  
file_path: long-lora/streaming_llm/utils.py
imports: import torch
  import argparse
  from transformers import AutoTokenizer, AutoModelForCausalLM
  import os.path
  import ssl
  import urllib.request
  import os
  import json
label_desc: Use image node_id 2 for calling a global function with example usage: load(model_name_or_path) and returns: model,  tokenizer