| # Importing libraries | |
| from transformers import PretrainedConfig | |
| class GPTConfig(PretrainedConfig): | |
| model_type = "custom_gpt" | |
| def __init__( | |
| self, | |
| block_size: int = 1024, | |
| vocab_size: int = 50304, | |
| n_layer: int = 12, | |
| n_head: int = 12, | |
| n_embd: int = 768, | |
| **kwargs, | |
| ): | |
| """ | |
| GPT configuration dataclass storing model hyperparameters. | |
| """ | |
| super().__init__(**kwargs) | |
| self.block_size = block_size | |
| self.vocab_size = vocab_size | |
| self.n_layer: int = n_layer | |
| self.n_head: int = n_head | |
| self.n_embd: int = n_embd | |