checking if other model thigns are needed

modeling_lang.py

@@ -21,7 +21,7 @@ class ExtendedMultitaskModelForTokenClassification(PreTrainedModel):
         self.model_floret = floret.load_model(self.config.config.filename)
 
     #
-    def forward(self, input_ids, attention_mask=None, **kwargs):
+    def forward(self, input_ids, **kwargs):
         if isinstance(input_ids, str):
             # If the input is a single string, make it a list for floret
             texts = [input_ids]
@@ -36,14 +36,6 @@ class ExtendedMultitaskModelForTokenClassification(PreTrainedModel):
             probabilities,
         )
 
-    # def state_dict(self, *args, **kwargs):
-    #     # Return an empty state dictionary
-    #     return {}
-    #
-    # def load_state_dict(self, state_dict, strict=True, **kwargs):
-    #     # Ignore loading since there are no parameters
-    #     pass
-
     @property
     def device(self):
         return next(self.parameters()).device