| from transformers.configuration_utils import PretrainedConfig | |
| from transformers.utils import logging | |
| logger = logging.get_logger(__name__) | |
| class RITAConfig(PretrainedConfig): | |
| model_type = "rita" | |
| def __init__( | |
| self, | |
| vocab_size=26, | |
| d_model=768, | |
| num_layers=12, | |
| max_seq_len=1024, | |
| num_heads=12, | |
| dropout=0., | |
| ff_ratio=4, | |
| eos_token_id=2, | |
| **kwargs, | |
| ): | |
| super().__init__(eos_token_id=eos_token_id, **kwargs) | |
| self.vocab_size = vocab_size | |
| self.d_model = d_model | |
| self.num_heads = num_heads | |
| self.d_feedforward = d_model*ff_ratio | |
| self.num_layers = num_layers | |
| self.max_seq_len=max_seq_len | |
| self.dropout = dropout | |
| self.eos_token_id=eos_token_id | |