code: 
  '''simple docstring'''
  
  from ...configuration_utils import PretrainedConfig
  from ...utils import logging
  
  
  _UpperCAmelCase   :      str 						=  logging.get_logger(__name__)
  
  _UpperCAmelCase   :      Optional[int] 						=  {
      """tau/splinter-base""": """https://huggingface.co/tau/splinter-base/resolve/main/config.json""",
      """tau/splinter-base-qass""": """https://huggingface.co/tau/splinter-base-qass/resolve/main/config.json""",
      """tau/splinter-large""": """https://huggingface.co/tau/splinter-large/resolve/main/config.json""",
      """tau/splinter-large-qass""": """https://huggingface.co/tau/splinter-large-qass/resolve/main/config.json""",
      # See all Splinter models at https://huggingface.co/models?filter=splinter
  }
  
  class 			UpperCAmelCase				(					a_ ):
  
  
  
  
  
  		"""simple docstring"""
  
  
  
  
  
  		A__  :   Union[str, Any]          =    'splinter'
  		def __init__(    self  ,					_snake_case=30522  ,					_snake_case=768  ,					_snake_case=12  ,					_snake_case=12  ,					_snake_case=3072  ,					_snake_case="gelu"  ,					_snake_case=0.1  ,					_snake_case=0.1  ,					_snake_case=512  ,					_snake_case=2  ,					_snake_case=0.02  ,					_snake_case=1E-12  ,					_snake_case=True  ,					_snake_case=0  ,					_snake_case=104  ,					**_snake_case  ,					)				->    Optional[Any]:
  				super().__init__(pad_token_id=_snake_case  ,					**_snake_case     )
  
  				_UpperCamelCase       : List[Any]    =      vocab_size
  				_UpperCamelCase       : Optional[int]    =      max_position_embeddings
  				_UpperCamelCase       : Union[str, Any]    =      hidden_size
  				_UpperCamelCase       : Tuple    =      num_hidden_layers
  				_UpperCamelCase       : List[Any]    =      num_attention_heads
  				_UpperCamelCase       : Tuple    =      intermediate_size
  				_UpperCamelCase       : List[str]    =      hidden_act
  				_UpperCamelCase       : Optional[Any]    =      hidden_dropout_prob
  				_UpperCamelCase       : List[Any]    =      attention_probs_dropout_prob
  				_UpperCamelCase       : Dict    =      initializer_range
  				_UpperCamelCase       : Any    =      type_vocab_size
  				_UpperCamelCase       : Optional[Any]    =      layer_norm_eps
  				_UpperCamelCase       : List[str]    =      use_cache
  				_UpperCamelCase       : Dict    =      question_token_id
  
  
  
  
style_context: 
  '''simple docstring'''
  
  _UpperCAmelCase   :      Optional[int] 						=  """
  # Transformers installation
  ! pip install transformers datasets evaluate
  # To install from source instead of the last release, comment the command above and uncomment the following one.
  # ! pip install git+https://github.com/huggingface/transformers.git
  """
  
  _UpperCAmelCase   :      Union[str, Any] 						=  [{"""type""": """code""", """content""": INSTALL_CONTENT}]
  _UpperCAmelCase   :      Union[str, Any] 						=  {
      """{processor_class}""": """FakeProcessorClass""",
      """{model_class}""": """FakeModelClass""",
      """{object_class}""": """FakeObjectClass""",
  }
  
  
  
  
  
  