code: def low_bit_sanity_check(model_path):
      invalidInputError(
          os.path.isdir(model_path),
          "model_path should be a valid directory path.",
      )
      invalidInputError(
          os.path.isfile(os.path.join(model_path, CONFIG_NAME)),
          "bigdl_config.json should be under your model directory,"
          "please check your input path.",
      )
      with open(os.path.join(model_path, CONFIG_NAME), "r") as f:
          _config = json.load(f)
  
      low_bit = _config.get("bigdl_transformers_low_bit", None)
      invalidInputError(
          low_bit,
          "Detect this model is not a low-bit model, Please use `optimize_model`"
          " with low_bit to get a low-bit model , and "
          " serialize the model using save_low_bit first.",
      )
      return low_bit
  
imports: import torch
  import os
  import json
  from .transformers import ggml_convert_low_bit
  from torch.nn.modules import Module
  from torch.nn.modules.module import _IncompatibleKeys
  from accelerate import init_empty_weights
  from accelerate.utils import set_module_tensor_to_device
  from bigdl.llm.ggml.quantize import ggml_tensor_qtype
  from bigdl.llm.utils.common import invalidInputError
  from bigdl.llm.transformers.utils import extract_local_archive_file, get_local_shard_files
  import transformers
  import warnings
  from transformers import PreTrainedModel
  from .utils.common import MuteHFLogger
  from .utils.lazy_load_torch import LazyLoadTensors
  from contextlib import ExitStack, contextmanager
label_desc: Use image node_id 2 for calling a global function with example usage: low_bit_sanity_check(model_path) and returns: low_bit