docstr: Test the serialization of the model and the loading of the quantized weights works with another config file
docstr_tok: ["Test","the","serialization","of","the","model","and","the","loading","of","the","quantized","weights","works","with","another","config","file"]
code: def test_change_loading_attributes(self):
      """
      Test the serialization of the model and the loading of the quantized weights works with another config file
      """
      with tempfile.TemporaryDirectory() as tmpdirname:
          self.quantized_model.save_pretrained(tmpdirname)
          if not self.use_exllama:
              self.check_quantized_layers_type(
                  self.quantized_model, "cuda-old"
              )
              # we need to put it directly to the gpu. Otherwise, we won't be able to initialize the exllama kernel
              quantized_model_from_saved = (
                  AutoModelForCausalLM.from_pretrained(
                      tmpdirname,
                      quantization_config=GPTQConfig(
                          use_exllama=True, bits=4
                      ),
                      device_map={"": 0},
                  )
              )
              self.assertEqual(
                  quantized_model_from_saved.config.quantization_config.bits,
                  self.bits,
              )
              self.check_quantized_layers_type(
                  quantized_model_from_saved, "exllama"
              )
              self.check_inference_correctness(
                  quantized_model_from_saved
              )
  
imports: import tempfile
  import unittest
  import pytest
  from transformers import AutoModelForCausalLM, AutoTokenizer, GPTQConfig
  from transformers.testing_utils import is_torch_available, require_accelerate, require_auto_gptq, require_optimum, require_torch_gpu, require_torch_multi_gpu, slow
label_desc: Use image node_id 11 for calling the GPTQTest obj's underlying member method code with example usage: obj.test_change_loading_attributes() without return types