| from transformers import PretrainedConfig |
|
|
| QWEN_TOKEN_ID = 151643 |
|
|
| AUTO_MAP = { |
| "AutoConfig": "configuration_modern_llm.ModernLLMConfig", |
| "AutoModelForCausalLM": "modeling_modern_llm.ModernLLMForCausalLM", |
| } |
|
|
|
|
| class ModernLLMConfig(PretrainedConfig): |
| model_type = "modern_llm" |
|
|
| def __init__( |
| self, |
| vocab_size: int = 151936, |
| hidden_size: int = 768, |
| intermediate_size: int = 2048, |
| num_hidden_layers: int = 12, |
| num_attention_heads: int = 12, |
| num_key_value_heads: int = 4, |
| max_position_embeddings: int = 2048, |
| rms_norm_eps: float = 1e-6, |
| rope_theta: float = 1000000.0, |
| pad_token_id: int = QWEN_TOKEN_ID, |
| bos_token_id: int = QWEN_TOKEN_ID, |
| eos_token_id: int = QWEN_TOKEN_ID, |
| **kwargs, |
| ): |
| self.vocab_size = vocab_size |
| 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.num_key_value_heads = num_key_value_heads |
| self.max_position_embeddings = max_position_embeddings |
| self.rms_norm_eps = rms_norm_eps |
| self.rope_theta = rope_theta |
| self.auto_map = dict(AUTO_MAP) |
| super().__init__( |
| pad_token_id=pad_token_id, |
| bos_token_id=bos_token_id, |
| eos_token_id=eos_token_id, |
| **kwargs, |
| ) |
|
|
