| from transformers import PretrainedConfig | |
| class GPTMoEMCTSConfig(PretrainedConfig): | |
| model_type = "gpt_moe_mcts" | |
| def __init__( | |
| self, | |
| vocab_size=50257, | |
| block_size=512, | |
| n_layer=6, | |
| n_head=4, | |
| n_embd=256, | |
| dropout=0.2, | |
| num_experts=3, | |
| expert_layers=3, | |
| block_size_q=32, | |
| block_size_kv=32, | |
| num_blocks_kv=4, | |
| **kwargs | |
| ): | |
| super().__init__(**kwargs) | |
| self.vocab_size = vocab_size | |
| self.block_size = block_size | |
| self.n_layer = n_layer | |
| self.n_head = n_head | |
| self.n_embd = n_embd | |
| self.dropout = dropout | |
| self.num_experts = num_experts | |
| self.expert_layers = expert_layers | |
| self.block_size_q = block_size_q | |
| self.block_size_kv = block_size_kv | |
| self.num_blocks_kv = num_blocks_kv |