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chore: import upstream snapshot with attribution
2026-07-13 11:57:37 +08:00

32 lines
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Python

# Example where we only want to overwrite the defaults of an init
from transformers.models.gemma.configuration_gemma import GemmaConfig
class NewModelConfig(GemmaConfig):
vocab_size: int = 256030
hidden_size: int = 64
intermediate_size: int = 90
num_hidden_layers: int = 28
num_attention_heads: int = 16
num_key_value_heads: int = 16
head_dim: int = 256
hidden_act: str = "gelu_pytorch_tanh"
hidden_activation: str | None = None
max_position_embeddings: int = 1500
initializer_range: float = 0.02
rms_norm_eps: float = 1e-6
use_cache: bool = True
pad_token_id: int = 0
eos_token_id: int = 1
bos_token_id: int = 2
tie_word_embeddings: bool = True
rope_parameters: dict | None = None
attention_bias: bool = False
attention_dropout: float = 0.0
use_bidirectional_attention: bool = False
@property
def num_heads(self):
return self.num_attention_heads