code: def check_llm_finetuning_adaption_prompt_parameters(
      config: "ModelConfig",
  ):
      """Checks that the adaption_prompt adapter is configured correctly.
  
      Adaption prompt is only supported for Llama models.
      """
      if config.model_type != MODEL_LLM:
          return
  
      if not config.adapter:
          return
  
      if config.adapter.type != "adaption_prompt":
          return
  
      from peft.tuners.adaption_prompt.config import (
          TRANSFORMERS_MODEL_CONFIG,
      )
  
      # Adaption Config is currently only supported for Llama model types
      model_config = _get_llm_model_config(config.base_model)
      if model_config.model_type not in TRANSFORMERS_MODEL_CONFIG:
          raise ConfigValidationError(
              f"Adaption prompt adapter is not supported for {model_config.model_type} model. "
              f"Supported model types are: {list(TRANSFORMERS_MODEL_CONFIG.keys())}."
          )
  
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 29 for calling a global function with example usage: check_llm_finetuning_adaption_prompt_parameters(config) without return types