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from transformers import T5Config
class SIPFinetuningModelConfig(T5Config):
model_type = "sip_finetune"
def __init__(self,
num_examples: int = 32,
prefix_length: int = 50,
random_selection: bool = True,
# don't change these unless you change what the prefix of the model is initialized with:
prefix_max_init_length: int = 70,
num_precomputed_examples: int = 400,
**kwargs):
# These are all about the initialization of the prefix.
self.num_examples = num_examples
self.prefix_length = prefix_length
self.random_selection = random_selection
self.prefix_max_init_length = prefix_max_init_length
self.num_precomputed_examples = num_precomputed_examples
super().__init__(**kwargs)
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