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configuration_siamese.py

@@ -7,7 +7,7 @@ class SiameseConfig(PretrainedConfig):
     def __init__(
         self,
         **kwargs):
-        super().__init__()
+        super().__init__(**kwargs)
 
 
 siamese_config = SiameseConfig()

modeling_siamese.py

@@ -1,5 +1,6 @@
 from transformers import PreTrainedModel, BertModel
 import torch
+from .configuration_siamese import SiameseConfig
 
 checkpoint = 'cointegrated/rubert-tiny'
 
@@ -36,6 +37,7 @@ second_model = SiameseNN()
 second_model.load_state_dict(torch.load('siamese_state'))
 
 class SiamseNNModel(PreTrainedModel):
+    config_class = SiameseConfig
     def __init__(self, config):
         super().__init__(config)
         self.model = second_model