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from transformers import PretrainedConfig
class SpecT1Config(PretrainedConfig):
model_type = "spect1"
def __init__(
self,
hidden_size=4096,
intermediate_size=11008,
num_attention_heads=32,
num_hidden_layers=36,
max_position_embeddings=32768,
vocab_size=151680,
attention_dropout=0.0,
hidden_act="silu",
max_window_layers=36,
rope_theta=640000,
sliding_window=32768,
attention_bias=True,
num_nextn_predict_layers=1,
initializer_range=0.02,
bos_token_id=151643,
eos_token_id=151645,
tie_word_embeddings=False,
**kwargs
):
super().__init__(**kwargs)
self.hidden_size = hidden_size
self.intermediate_size = intermediate_size
self.num_attention_heads = num_attention_heads
self.num_hidden_layers = num_hidden_layers
self.max_position_embeddings = max_position_embeddings
self.vocab_size = vocab_size
self.attention_dropout = attention_dropout
self.hidden_act = hidden_act
self.max_window_layers = max_window_layers
self.rope_theta = rope_theta
self.sliding_window = sliding_window
self.attention_bias = attention_bias
self.num_nextn_predict_layers = num_nextn_predict_layers
self.initializer_range = initializer_range
self.bos_token_id = bos_token_id
self.eos_token_id = eos_token_id
self.tie_word_embeddings = tie_word_embeddings
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