| """gLM2 model configuration""" | |
| from typing import Optional | |
| from transformers import PretrainedConfig | |
| from transformers.utils import logging | |
| logger = logging.get_logger(__name__) | |
| class gLM2Config(PretrainedConfig): | |
| model_type = "gLM2" | |
| def __init__( | |
| self, | |
| dim: int = 640, | |
| depth: int = 30, | |
| heads: int = 10, | |
| vocab_size: int = 37, | |
| swiglu_multiple_of: int = 256, | |
| ffn_dim_multiplier: Optional[float] = None, | |
| norm_eps: float = 1e-5, | |
| **kwargs | |
| ): | |
| super().__init__(**kwargs) | |
| self.dim = dim | |
| self.depth = depth | |
| self.heads = heads | |
| self.vocab_size = vocab_size | |
| self.swiglu_multiple_of = swiglu_multiple_of | |
| self.ffn_dim_multiplier = ffn_dim_multiplier | |
| self.norm_eps = norm_eps | |
| self.auto_map = { | |
| "AutoConfig": "configuration_glm2.gLM2Config", | |
| "AutoModel": "modeling_glm2.gLM2Model", | |
| "AutoModelForMaskedLM": "modeling_glm2.gLM2ForMaskedLM" | |
| } | |