docstr: Setup quantized model from loaded model
code: def setUp(self):
      """
      Setup quantized model from loaded model
      """
      from transformers import AutoModelForCausalLM, AutoTokenizer
  
      super().setUp()
  
      # Models and tokenizer
      self.model_fp16 = AutoModelForCausalLM.from_pretrained(
          self.model_name, torch_dtype=torch.float16, device_map="auto"
      )
  
      self.bnb_quantization_config = BnbQuantizationConfig(
          load_in_4bit=True
      )
  
      self.model_4bit = AutoModelForCausalLM.from_pretrained(
          self.model_name, torch_dtype=torch.float16
      )
      self.model_4bit = load_and_quantize_model(
          self.model_4bit, self.bnb_quantization_config
      )
  
      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 Bnb4BitTestLoadedModel obj's underlying member method code with example usage: obj.setUp() without return types