quick fix from pretrained. (PaddlePaddle#8487)

paddlenlp/transformers/model_utils.py

@@ -798,7 +798,7 @@ def _load_state_dict_into_meta_model(
 
     dtype = convert_np_dtype_to_dtype_(dtype)
     error_msgs = []
-
+    model_state_dict = model.state_dict()
     for param_name, param in state_dict.items():
         # First part of the test is always true as loaded_state_dict_keys always contains state_dict keys.
         if param_name not in loaded_state_dict_keys or param_name not in expected_keys:
@@ -833,7 +833,7 @@ def _load_state_dict_into_meta_model(
             if old_param is not None:
                 param = param.astype(dtype=old_param.dtype)
         with paddle.no_grad():
-            model.state_dict()[param_name].get_tensor()._share_data_with(param.value().get_tensor())
+            model_state_dict[param_name].get_tensor()._share_data_with(param.value().get_tensor())
             param.value().get_tensor()._clear()
     return error_msgs
 
@@ -1890,7 +1890,7 @@ def _find_mismatched_keys(
                 if (
                     shard_file.endswith(".safetensors")
                     and config.tensor_parallel_degree > 1
-                    and "tp" not in shard_file
+                    and "tp" not in os.path.spilt(shard_file)[-1]
                 ):
                     pre_tensor_parallel_split = True
                     assert loaded_keys is not None, "loaded_keys is not None."