from dataclasses import dataclass
from transformers import PretrainedConfig

@dataclass
class OrcaleSeekConfig:
    model_type: str = "orcaleseek"
    vocab_size: int = 50257
    n_embd: int = 768
    n_layer: int = 12
    n_head: int = 12
    n_inner: int = 3072
    activation_function: str = "gelu_new"
    resid_pdrop: float = 0.1
    embd_pdrop: float = 0.1
    attn_pdrop: float = 0.1
    layer_norm_epsilon: float = 1e-5
    initializer_range: float = 0.02
    scale_attn_weights: bool = True
    use_cache: bool = True
    bos_token_id: int = 50256
    eos_token_id: int = 50256
    architectures = ["OrcaleSeekForCausalLM"]
    
    def to_hf_config(self):
        return PretrainedConfig(**self.__dict__)