| from transformers import PretrainedConfig | |
| class STLEncoderConfig(PretrainedConfig): | |
| model_type = "stl_encoder" | |
| def __init__( | |
| self, | |
| vocab_size=35, | |
| hidden_size=1024, | |
| num_hidden_layers=12, | |
| num_attention_heads=16, | |
| intermediate_size=4096, | |
| max_position_embeddings=512, | |
| embedding_dim_target=1024, | |
| **kwargs | |
| ): | |
| super().__init__(**kwargs) | |
| self.vocab_size = vocab_size | |
| self.hidden_size = hidden_size | |
| self.num_hidden_layers = num_hidden_layers | |
| self.num_attention_heads = num_attention_heads | |
| self.intermediate_size = intermediate_size | |
| self.max_position_embeddings = max_position_embeddings | |
| self.embedding_dim_target = embedding_dim_target |