| """Configuration for the fixed Purrence-3M inference architecture.""" |
| from dataclasses import asdict |
| from transformers import PretrainedConfig |
| from .purrence_core import ModelConfig |
|
|
|
|
| class PurrenceConfig(PretrainedConfig): |
| model_type = "purrence" |
|
|
| def __init__(self, **kwargs): |
| dimensions = asdict(ModelConfig()) |
| for name, default in dimensions.items(): |
| dimensions[name] = kwargs.pop(name, default) |
| ModelConfig(**dimensions).validate() |
| kwargs.setdefault("bos_token_id", 2047) |
| kwargs.setdefault("eos_token_id", 2047) |
| kwargs.setdefault("pad_token_id", 2047) |
| kwargs.setdefault("tie_word_embeddings", True) |
| super().__init__(**kwargs) |
| for name, value in dimensions.items(): |
| setattr(self, name, value) |
| self.max_position_embeddings = self.max_seq_len |
| self.use_cache = False |
|
|
