



'''simple docstring'''




from ...configuration_utils import PretrainedConfig
from ...utils import logging


UpperCamelCase__			:      Tuple        =					logging.get_logger(__name__)

UpperCamelCase__			:      List[Any]        =					{
    '''microsoft/biogpt''': '''https://huggingface.co/microsoft/biogpt/resolve/main/config.json''',
    # See all BioGPT models at https://huggingface.co/models?filter=biogpt
}






class 		_UpperCamelCase    (				__a       ):


			'''simple docstring'''

			_A :						List[Any]            =						'''biogpt'''

			def __init__(				self	:					Tuple				,	lowerCAmelCase__	:					int=4_2_3_8_4				,	lowerCAmelCase__	:					Optional[Any]=1_0_2_4				,	lowerCAmelCase__	:					Union[str, Any]=2_4				,	lowerCAmelCase__	:					str=1_6				,	lowerCAmelCase__	:					Any=4_0_9_6				,	lowerCAmelCase__	:					Optional[int]="gelu"				,	lowerCAmelCase__	:					int=0.1				,	lowerCAmelCase__	:					int=0.1				,	lowerCAmelCase__	:					str=1_0_2_4				,	lowerCAmelCase__	:					List[Any]=0.02				,	lowerCAmelCase__	:					str=1E-12				,	lowerCAmelCase__	:					int=True				,	lowerCAmelCase__	:					Union[str, Any]=True				,	lowerCAmelCase__	:					int=0.0				,	lowerCAmelCase__	:					Tuple=0.0				,	lowerCAmelCase__	:					str=1				,	lowerCAmelCase__	:					str=0				,	lowerCAmelCase__	:					int=2				,	**lowerCAmelCase__	:					Dict				,	):





					"""simple docstring"""






					__SCREAMING_SNAKE_CASE			:						Tuple       			=						vocab_size
					__SCREAMING_SNAKE_CASE			:						Optional[int]       			=						max_position_embeddings
					__SCREAMING_SNAKE_CASE			:						Any       			=						hidden_size
					__SCREAMING_SNAKE_CASE			:						str       			=						num_hidden_layers
					__SCREAMING_SNAKE_CASE			:						Dict       			=						num_attention_heads
					__SCREAMING_SNAKE_CASE			:						Dict       			=						intermediate_size
					__SCREAMING_SNAKE_CASE			:						Optional[Any]       			=						hidden_act
					__SCREAMING_SNAKE_CASE			:						Dict       			=						hidden_dropout_prob
					__SCREAMING_SNAKE_CASE			:						int       			=						attention_probs_dropout_prob
					__SCREAMING_SNAKE_CASE			:						List[str]       			=						initializer_range
					__SCREAMING_SNAKE_CASE			:						Union[str, Any]       			=						layer_norm_eps
					__SCREAMING_SNAKE_CASE			:						Tuple       			=						scale_embedding
					__SCREAMING_SNAKE_CASE			:						List[Any]       			=						use_cache
					__SCREAMING_SNAKE_CASE			:						Optional[int]       			=						layerdrop
					__SCREAMING_SNAKE_CASE			:						Any       			=						activation_dropout
					super().__init__(pad_token_id=_lowercase				,	bos_token_id=_lowercase				,	eos_token_id=_lowercase				,	**_lowercase		)
UpperCAmelCase_           =				'''
# Transformers installation
! pip install transformers datasets
# 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_           =				[{'''type''': '''code''', '''content''': INSTALL_CONTENT}]
UpperCAmelCase_           =				{
    '''{processor_class}''': '''FakeProcessorClass''',
    '''{model_class}''': '''FakeModelClass''',
    '''{object_class}''': '''FakeObjectClass''',
}