| from transformers import PretrainedConfig | |
| class DiffusionConfig(PretrainedConfig): | |
| model_type = "gpt2" | |
| def __init__( | |
| self, | |
| vocab_size=425, | |
| d_model=512, | |
| n_heads=16, | |
| n_layers=6, | |
| dropout=0.1, | |
| max_len=2250, | |
| num_steps=1000, | |
| pad_token=0, | |
| **kwargs | |
| ): | |
| super().__init__(**kwargs) | |
| self.vocab_size = vocab_size | |
| self.d_model = d_model | |
| self.n_heads = n_heads | |
| self.n_layers = n_layers | |
| self.dropout = dropout | |
| self.max_len = max_len | |
| self.num_steps = num_steps | |
| self.pad_token = pad_token | |