code: def check_llm_finetuning_output_feature_config(
      config: "ModelConfig",
  ):  # noqa: F821
      """Checks that the output feature config for LLM finetuning is valid."""
      if config.model_type != MODEL_LLM:
          return
  
      if config.trainer.type != "finetune":
          return
  
      if config.output_features[0].type != TEXT:
          raise ConfigValidationError(
              "LLM finetuning requires the output feature to be a text feature. If you are trying to use a different "
              "output feature type such as category or binary, please change the output feature type to text."
          )
  
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 25 for calling a global function with example usage: check_llm_finetuning_output_feature_config(config) without return types