class_docstr: Structured Model Card class. Store model card as well as methods for loading/downloading/saving model cards.
  
  Please read the following paper for details and explanation on the sections: "Model Cards for Model Reporting" by
  Margaret Mitchell, Simone Wu, Andrew Zaldivar, Parker Barnes, Lucy Vasserman, Ben Hutchinson, Elena Spitzer,
  Inioluwa Deborah Raji and Timnit Gebru for the proposal behind model cards. Link: https://arxiv.org/abs/1810.03993
  
  Note: A model card can be loaded and saved to disk.
class_docstr_tok: ["Structured","Model","Card","class",".","Store","model","card","as","well","as","methods","for","loading\/downloading\/saving","model","cards",".","Please","read","the","following","paper","for","details","and","explanation","on","the","sections",":","``","Model","Cards","for","Model","Reporting","''","by","Margaret","Mitchell",",","Simone","Wu",",","Andrew","Zaldivar",",","Parker","Barnes",",","Lucy","Vasserman",",","Ben","Hutchinson",",","Elena","Spitzer",",","Inioluwa","Deborah","Raji","and","Timnit","Gebru","for","the","proposal","behind","model","cards",".","Link",":","https",":","\/\/arxiv.org\/abs\/1810.03993","Note",":","A","model","card","can","be","loaded","and","saved","to","disk","."]
docstr: Serializes this instance to a Python dictionary.
docstr_tok: ["Serializes","this","instance","to","a","Python","dictionary","."]
code: def to_dict(self):
      """Serializes this instance to a Python dictionary."""
      output = copy.deepcopy(self.__dict__)
      return output
  
imports: import copy
  import json
  import os
  import warnings
  from dataclasses import dataclass
  from pathlib import Path
  from typing import Any, Dict, List, Optional, Union
  import requests
  import yaml
  from huggingface_hub import model_info
  from huggingface_hub.utils import HFValidationError
  from .None import __version__
  from .models.auto.modeling_auto import MODEL_FOR_AUDIO_CLASSIFICATION_MAPPING_NAMES, MODEL_FOR_CAUSAL_LM_MAPPING_NAMES, MODEL_FOR_CTC_MAPPING_NAMES, MODEL_FOR_IMAGE_CLASSIFICATION_MAPPING_NAMES, MODEL_FOR_IMAGE_SEGMENTATION_MAPPING_NAMES, MODEL_FOR_MASKED_LM_MAPPING_NAMES, MODEL_FOR_OBJECT_DETECTION_MAPPING_NAMES, MODEL_FOR_QUESTION_ANSWERING_MAPPING_NAMES, MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING_NAMES, MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING_NAMES, MODEL_FOR_SPEECH_SEQ_2_SEQ_MAPPING_NAMES, MODEL_FOR_TABLE_QUESTION_ANSWERING_MAPPING_NAMES, MODEL_FOR_TOKEN_CLASSIFICATION_MAPPING_NAMES, MODEL_FOR_ZERO_SHOT_IMAGE_CLASSIFICATION_MAPPING_NAMES
  from .training_args import ParallelMode
  from .utils import MODEL_CARD_NAME, cached_file, is_datasets_available, is_offline_mode, is_tf_available, is_tokenizers_available, is_torch_available, logging
label_desc: Use image node_id 8 for calling the ModelCard obj's underlying member method code with example usage: obj.to_dict() and returns: output