def test_llm_skip(self):
        r"""
        A simple test to check if `llm_int8_skip_modules` works as expected
        """
        import bitsandbytes as bnb

        quantization_config = BitsAndBytesConfig(load_in_8bit=True, llm_int8_skip_modules=["classifier"])
        seq_classification_model = AutoModelForSequenceClassification.from_pretrained(
            "roberta-large-mnli", quantization_config=quantization_config
        )
        self.assertTrue(seq_classification_model.roberta.encoder.layer[0].output.dense.weight.dtype == torch.int8)
        self.assertTrue(
            isinstance(seq_classification_model.roberta.encoder.layer[0].output.dense, bnb.nn.Linear8bitLt)
        )

        self.assertTrue(isinstance(seq_classification_model.classifier.dense, nn.Linear))
        self.assertTrue(seq_classification_model.classifier.dense.weight.dtype != torch.int8)
        self.assertTrue(isinstance(seq_classification_model.classifier.out_proj, nn.Linear))
        self.assertTrue(seq_classification_model.classifier.out_proj != torch.int8)

        A simple test to check if `llm_int8_skip_modules` works as expected
        
dpkd/transformers/tests/quantization/bnb/test_mixed_int8.py