checking if other model thigns are needed

modeling_lang.py

@@ -48,11 +48,11 @@ class ExtendedMultitaskModelForTokenClassification(PreTrainedModel):
     def device(self):
         return next(self.parameters()).device
 
-    # @classmethod
-    # def from_pretrained(cls, *args, **kwargs):
-    #     # print("Ignoring weights and using custom initialization.")
-    #     # Manually create the config
-    #     config = ImpressoConfig(**kwargs)
-    #     # Pass the manually created config to the class
-    #     model = cls(config)
-    #     return model
+    @classmethod
+    def from_pretrained(cls, *args, **kwargs):
+        # print("Ignoring weights and using custom initialization.")
+        # Manually create the config
+        config = ImpressoConfig(**kwargs)
+        # Pass the manually created config to the class
+        model = cls(config)
+        return model