update

src/transformers/modeling_utils.py

@@ -4348,28 +4348,6 @@ def _load_pretrained_model(
         # Now assign the updated list to loaded_keys
         loaded_keys = updated_loaded_keys
 
-        def _fix_key(key):
-            if "beta" in key:
-                return key.replace("beta", "bias")
-            if "gamma" in key:
-                return key.replace("gamma", "weight")
-
-            # to avoid logging parametrized weight norm renaming
-            if hasattr(nn.utils.parametrizations, "weight_norm"):
-                if "weight_g" in key:
-                    return key.replace("weight_g", "parametrizations.weight.original0")
-                if "weight_v" in key:
-                    return key.replace("weight_v", "parametrizations.weight.original1")
-            else:
-                if "parametrizations.weight.original0" in key:
-                    return key.replace("parametrizations.weight.original0", "weight_g")
-                if "parametrizations.weight.original1" in key:
-                    return key.replace("parametrizations.weight.original1", "weight_v")
-            return key
-
-        original_loaded_keys = loaded_keys
-        loaded_keys = [_fix_key(key) for key in loaded_keys]
-
         if len(prefix) > 0:
             has_prefix_module = any(s.startswith(prefix) for s in loaded_keys)
             expects_prefix_module = any(s.startswith(prefix)