code: def _load_config(
      model_path,
      model_filename,
      safetensors=False,
      trust_remote_code=True,
      max_new_tokens=4096,
  ):
      # [STEP 1] Download model if path is not a directory
      if not os.path.isdir(model_path):
          ignore_patterns = ["*msgpack*", "*h5*"]
          if safetensors:
              ignore_patterns.extend(["*.pt*", "*.bin*"])
          else:
              ignore_patterns.append("*.safetensors*")
  
          model_path = snapshot_download(
              model_path, ignore_patterns=ignore_patterns
          )
  
      if model_filename != "":
          model_weights_path = model_path + f"/{model_filename}"
      else:
          model_weights_path = model_path
  
      # Load model config and set max generation length
      max_new_tokens = (
          2048 if max_new_tokens is None else max_new_tokens
      )
      config = AutoConfig.from_pretrained(
          model_path, trust_remote_code=trust_remote_code
      )
      config.max_new_tokens = max_new_tokens
  
      return model_weights_path, config
  
file_path: BigDL/python/llm/src/bigdl/llm/transformers/awq/awq.py
imports: import gc
  import os
  from tqdm import tqdm
  import torch
  import torch.nn
  from transformers.models.bloom.modeling_bloom import BloomForCausalLM
  from transformers.models.opt.modeling_opt import OPTForCausalLM
  from transformers.models.llama.modeling_llama import LlamaForCausalLM
  from transformers.models.bloom.modeling_bloom import BloomBlock
  from transformers import AwqConfig, AutoConfig
  from bigdl.llm.transformers.awq.linear import WQLinear_GEMM, WQLinear_GEMV
  from huggingface_hub import snapshot_download
  from bigdl.llm.utils.common import invalidInputError
label_desc: Use image node_id 2 for calling a global function with example usage: _load_config(model_path, model_filename, safetensors, trust_remote_code, max_new_tokens) and returns: model_weights_path,  config