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from transformers import T5Config |
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class SIPFinetuningModelConfig(T5Config): |
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model_type = "sip_finetune" |
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def __init__(self, |
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num_examples: int = 32, |
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prefix_length: int = 50, |
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random_selection: bool = True, |
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prefix_max_init_length: int = 70, |
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num_precomputed_examples: int = 400, |
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**kwargs): |
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self.num_examples = num_examples |
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self.prefix_length = prefix_length |
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self.random_selection = random_selection |
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self.prefix_max_init_length = prefix_max_init_length |
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self.num_precomputed_examples = num_precomputed_examples |
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super().__init__(**kwargs) |
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