code: def set_llm_parameters(config: "ModelConfig") -> None:
      if config.model_type != MODEL_LLM:
          return
  
      # Set preprocessing parameters for text features for LLM model type
      _set_llm_tokenizers(config)
  
      # Set max_new_tokens in generation config to the max sequence length of the output features
      _set_generation_max_new_tokens(config)
  
      # HACK(Arnav): Set Mixtral target modules when using LoRA
      # GitHub issue: https://github.com/ludwig-ai/ludwig/issues/3853
      _set_mixtral_target_modules(config)
  
imports: import copy
  import logging
  import sys
  import warnings
  from typing import Any, Dict, List, Mapping, Set, TYPE_CHECKING
  from marshmallow import ValidationError
  from transformers import AutoConfig
  from ludwig.api_annotations import DeveloperAPI
  from ludwig.constants import CATEGORY, COMBINED, DECODER, DEFAULTS, ENCODER, GRID_SEARCH, INPUT_FEATURES, LOSS, MODEL_ECD, MODEL_LLM, OUTPUT_FEATURES, PARAMETERS, PREPROCESSING, SEQUENCE, SPACE, TEXT, TYPE
  from ludwig.features.feature_utils import compute_feature_hash
  from ludwig.schema.features.utils import output_config_registry
  from ludwig.schema.hyperopt.scheduler import BaseHyperbandSchedulerConfig
  from ludwig.schema.llms.generation import LLMGenerationConfig
  from ludwig.schema.trainer import ECDTrainerConfig
  from ludwig.types import HyperoptConfigDict, ModelConfigDict
  from ludwig.utils.data_utils import get_sanitized_feature_name
  from ludwig.utils.llm_utils import get_context_len
label_desc: Use image node_id 12 for calling a global function with example usage: set_llm_parameters(config) without return types