code: def check_qlora_requirements(
      config: "ModelConfig",
  ) -> None:  # noqa: F821
      """Checks that all the necessary settings are in place for QLoRA."""
      if (
          config.model_type != MODEL_LLM
          or config.trainer.type == "none"
      ):
          return
  
      if config.quantization and (
          not config.adapter or config.adapter.type != "lora"
      ):
          raise ConfigValidationError(
              "Fine-tuning and LLM with quantization requires using the 'lora' adapter"
          )
  
imports: from abc import ABC, abstractmethod
  from re import findall
  from typing import Callable, TYPE_CHECKING
  from transformers import AutoConfig
  from ludwig.api_annotations import DeveloperAPI
  from ludwig.constants import AUDIO, BINARY, CATEGORY, IMAGE, IN_MEMORY, MIN_QUANTIZATION_BITS_FOR_MERGE_AND_UNLOAD, MODEL_ECD, MODEL_GBM, MODEL_LLM, NUMBER, SEQUENCE, SET, TEXT, TIMESERIES, VECTOR
  from ludwig.error import ConfigValidationError
  from ludwig.utils.metric_utils import get_feature_to_metric_names_map_from_feature_collection
  from ludwig.utils.misc_utils import merge_dict
label_desc: Use image node_id 33 for calling a global function with example usage: check_qlora_requirements(config) without return types