def get_quant_model(
        self, model: HfModelHandler, config: type[BasePassConfig], output_model_path: str
    ) -> tuple[HfModelHandler, "PreTrainedModel", dict, list[str]]:
        """Get the model handler, LoRA model for QLoRA fine-tuning.

        :param model: The input model handler.
        :param config: The config for the pass run.
        :param output_model_path: The path to save the output model to.
        :return: The new model handler, LoRA model, quantization config and list of quantized modules.
        """
        raise NotImplementedError
Get the model handler, LoRA model for QLoRA fine-tuning.

        :param model: The input model handler.
        :param config: The config for the pass run.
        :param output_model_path: The path to save the output model to.
        :return: The new model handler, LoRA model, quantization config and list of quantized modules.
        
olive/passes/pytorch/lora.py