| from transformers import PretrainedConfig | |
| class NanoGPTConfig(PretrainedConfig): | |
| model_type = "nanogpt" | |
| def __init__( | |
| self, | |
| sequence_len: int = 1024, | |
| vocab_size: int = 50304, | |
| n_layer: int = 12, | |
| n_head: int = 6, | |
| n_kv_head: int = 6, | |
| n_embd: int = 768, | |
| **kwargs, | |
| ): | |
| self.sequence_len = sequence_len | |
| self.vocab_size = vocab_size | |
| self.n_layer = n_layer | |
| self.n_head = n_head | |
| self.n_kv_head = n_kv_head | |
| self.n_embd = n_embd | |
| super().__init__(**kwargs) | |