| from transformers import PretrainedConfig | |
| class BertItalianoConfig(PretrainedConfig): | |
| model_type="BertItaliano" | |
| def __init__( | |
| self, | |
| attention_probs_dropout_prob: float = 0.1, | |
| gradient_checkpointing: bool = False, | |
| hidden_act="gelu", | |
| hidden_dropout_prob: float = 0.1, | |
| hidden_size: int = 768, | |
| initializer_range: float = 0.02, | |
| intermediate_size: int = 3072, | |
| layer_norm_eps: float = 1e-12, | |
| max_position_embeddings: int = 512, | |
| num_attention_heads: int = 12, | |
| num_hidden_layers: int = 12, | |
| pad_token_id: int = 0, | |
| position_embedding_type="absolute", | |
| transformers_version="4.10.3", | |
| torch_dtype="float32", | |
| type_vocab_size: int = 2, | |
| use_cache: bool = True, | |
| vocab_size: int = 32102, | |
| **kwargs, | |
| ): | |
| self.attention_probs_dropout_prob = attention_probs_dropout_prob | |
| self.gradient_checkpointing = gradient_checkpointing | |
| self.hidden_act = hidden_act | |
| self.hidden_dropout_prob = hidden_dropout_prob | |
| self.hidden_size = hidden_size | |
| self.initializer_range = initializer_range | |
| self.intermediate_size = intermediate_size | |
| self.layer_norm_eps = layer_norm_eps | |
| self.max_position_embeddings = max_position_embeddings | |
| self.num_attention_heads = num_attention_heads | |
| self.num_hidden_layers = num_hidden_layers | |
| self.pad_token_id = pad_token_id | |
| self.position_embedding_type = position_embedding_type | |
| self.transformers_version = transformers_version | |
| self.torch_dtype = torch_dtype | |
| self.type_vocab_size = type_vocab_size | |
| self.use_cache = use_cache | |
| self.vocab_size = vocab_size | |
| super().__init__(**kwargs) | |