code: def setUp(self):
      from huggingface_hub import hf_hub_download
      from transformers import (
          AutoConfig,
          AutoModelForCausalLM,
          AutoTokenizer,
      )
  
      super().setUp()
  
      # Models and tokenizer
      self.model_fp16 = AutoModelForCausalLM.from_pretrained(
          self.model_name, torch_dtype=torch.float16, device_map="auto"
      )
  
      # create model on meta device
      with init_empty_weights():
          self.model_4bit = AutoModelForCausalLM.from_config(
              AutoConfig.from_pretrained(self.model_name)
          )
  
      self.model_4bit.tie_weights()
      self.weights_location = hf_hub_download(
          self.model_name, "pytorch_model.bin"
      )
      self.bnb_quantization_config = BnbQuantizationConfig(
          load_in_4bit=True
      )
  
      self.model_4bit = load_and_quantize_model(
          self.model_4bit,
          self.bnb_quantization_config,
          weights_location=self.weights_location,
          device_map={"": 0},
          no_split_module_classes=["BloomBlock"],
      )
  
      self.tokenizer = AutoTokenizer.from_pretrained(
          "bigscience/bloom-1b7"
      )
  
imports: import gc
  import tempfile
  import unittest
  import torch
  import torch.nn
  from accelerate import Accelerator, init_empty_weights
  from accelerate.test_utils import require_bnb, require_cuda, require_huggingface_suite, require_multi_gpu, slow
  from accelerate.utils.bnb import load_and_quantize_model
  from accelerate.utils.dataclasses import BnbQuantizationConfig
label_desc: Use image node_id 1 for calling the Bnb4BitEmptyModelTest obj's underlying member method code with example usage: obj.setUp() without return types