| from transformers.configuration_utils import PretrainedConfig | |
| class CapAIConfig(PretrainedConfig): | |
| model_type = "capai" | |
| keys_to_ignore_at_inference = ["past_key_values"] | |
| def __init__( | |
| self, | |
| vocab_size=64000, | |
| hidden_size=5120, | |
| intermediate_size=13696, | |
| num_hidden_layers=40, | |
| num_attention_heads=40, | |
| hidden_act="silu", | |
| model_max_length=4096, | |
| initializer_range=0.02, | |
| rms_norm_eps=1e-6, | |
| use_cache=True, | |
| pad_token_id=0, | |
| bos_token_id=1, | |
| eos_token_id=2, | |
| tie_word_embeddings=False, | |
| gradient_checkpointing=False, | |
| z_loss_weight=0, | |
| **kwargs, | |
| ): | |
| self.vocab_size = vocab_size | |
| self.model_max_length = model_max_length | |
| self.hidden_size = hidden_size | |
| self.intermediate_size = intermediate_size | |
| self.num_hidden_layers = num_hidden_layers | |
| self.num_attention_heads = num_attention_heads | |
| self.hidden_act = hidden_act | |
| self.initializer_range = initializer_range | |
| self.rms_norm_eps = rms_norm_eps | |
| self.use_cache = use_cache | |
| self.z_loss_weight = z_loss_weight | |
| self.gradient_checkpointing = (gradient_checkpointing,) | |
| super().__init__( | |
| pad_token_id=pad_token_id, | |
| bos_token_id=bos_token_id, | |
| eos_token_id=eos_token_id, | |
| tie_word_embeddings=tie_word_embeddings, | |
| **kwargs, | |
| ) | |