code: def get_model_modules() -> List[str]:
      """Get all the model modules inside the transformers library (except deprecated models)."""
      _ignore_modules = [
          "modeling_auto",
          "modeling_encoder_decoder",
          "modeling_marian",
          "modeling_mmbt",
          "modeling_outputs",
          "modeling_retribert",
          "modeling_utils",
          "modeling_flax_auto",
          "modeling_flax_encoder_decoder",
          "modeling_flax_utils",
          "modeling_speech_encoder_decoder",
          "modeling_flax_speech_encoder_decoder",
          "modeling_flax_vision_encoder_decoder",
          "modeling_timm_backbone",
          "modeling_tf_auto",
          "modeling_tf_encoder_decoder",
          "modeling_tf_outputs",
          "modeling_tf_pytorch_utils",
          "modeling_tf_utils",
          "modeling_tf_vision_encoder_decoder",
          "modeling_vision_encoder_decoder",
      ]
      modules = []
      for model in dir(transformers.models):
          # There are some magic dunder attributes in the dir, we ignore them
          if model == "deprecated" or model.startswith("__"):
              continue
  
          model_module = getattr(transformers.models, model)
          for submodule in dir(model_module):
              if (
                  submodule.startswith("modeling")
                  and submodule not in _ignore_modules
              ):
                  modeling_module = getattr(model_module, submodule)
                  if inspect.ismodule(modeling_module):
                      modules.append(modeling_module)
      return modules
  
imports: import inspect
  import os
  import re
  import sys
  import types
  import warnings
  from collections import OrderedDict
  from difflib import get_close_matches
  from pathlib import Path
  from typing import List, Tuple
  from transformers import is_flax_available, is_tf_available, is_torch_available
  from transformers.models.auto import get_values
  from transformers.models.auto.configuration_auto import CONFIG_MAPPING_NAMES
  from transformers.models.auto.feature_extraction_auto import FEATURE_EXTRACTOR_MAPPING_NAMES
  from transformers.models.auto.image_processing_auto import IMAGE_PROCESSOR_MAPPING_NAMES
  from transformers.models.auto.processing_auto import PROCESSOR_MAPPING_NAMES
  from transformers.models.auto.tokenization_auto import TOKENIZER_MAPPING_NAMES
  from transformers.utils import ENV_VARS_TRUE_VALUES, direct_transformers_import
label_desc: Use image node_id 3 for calling a global function with example usage: get_model_modules() and returns: modules