diff --git a/tutorials/source_en/use/saving_and_loading_model_parameters.md b/tutorials/source_en/use/saving_and_loading_model_parameters.md
index ba46b8a89a72720b6771bb073133b8abd525039e..88d80140d166b2ab3309a71335de78899101b7b5 100644
--- a/tutorials/source_en/use/saving_and_loading_model_parameters.md
+++ b/tutorials/source_en/use/saving_and_loading_model_parameters.md
@@ -143,14 +143,14 @@ the code is as follows:
 ```python
 from mindspore.train.serialization import export
 import numpy as np
-net = ResNet50()
+resnet = ResNet50()
 # return a parameter dict for model
-param_dict = load_checkpoint("resnet50-2_32.ckpt", net=resnet)
+param_dict = load_checkpoint("resnet50-2_32.ckpt")
 # load the parameter into net
-load_param_into_net(net)
+load_param_into_net(resnet, param_dict)
 input = np.random.uniform(0.0, 1.0, size = [32, 3, 224, 224]).astype(np.float32)
-export(net, input, file_name = 'resnet50-2_32.pb', file_format = 'GEIR')
+export(resnet, input, file_name = 'resnet50-2_32.pb', file_format = 'GEIR')
 ```
 Before using the `export` interface, you need to import` mindspore.train.serialization`.
 The `input` parameter is used to specify the input shape and data type of the exported model.
-If you want to export the ONNX model, you only need to specify the `file_format` parameter in the` export` interface as ONNX: `file_format = 'ONNX'`.
\ No newline at end of file
+If you want to export the ONNX model, you only need to specify the `file_format` parameter in the` export` interface as ONNX: `file_format = 'ONNX'`.
diff --git a/tutorials/source_zh_cn/use/saving_and_loading_model_parameters.md b/tutorials/source_zh_cn/use/saving_and_loading_model_parameters.md
index 50f901b30a83ae3f9cecbbb97d502b775d7ea757..0bdf8fa7f711904001848ef415fdb693ef694d58 100644
--- a/tutorials/source_zh_cn/use/saving_and_loading_model_parameters.md
+++ b/tutorials/source_zh_cn/use/saving_and_loading_model_parameters.md
@@ -143,14 +143,14 @@ model.train(epoch, dataset)
 ```python
 from mindspore.train.serialization import export
 import numpy as np
-net = ResNet50()
+resnet = ResNet50()
 # return a parameter dict for model
-param_dict = load_checkpoint("resnet50-2_32.ckpt", net=resnet)
+param_dict = load_checkpoint("resnet50-2_32.ckpt")
 # load the parameter into net
-load_param_into_net(net)
+load_param_into_net(resnet, param_dict)
 input = np.random.uniform(0.0, 1.0, size = [32, 3, 224, 224]).astype(np.float32)
-export(net, input, file_name = 'resnet50-2_32.pb', file_format = 'GEIR')
+export(resnet, input, file_name = 'resnet50-2_32.pb', file_format = 'GEIR')
 ```
 使用`export`接口之前，需要先导入`mindspore.train.serialization`。
 `input`用来指定导出模型的输入shape以及数据类型。
-如果要导出ONNX模型，只需要将`export`接口中的`file_format`参数指定为ONNX即可：`file_format = 'ONNX'`。
\ No newline at end of file
+如果要导出ONNX模型，只需要将`export`接口中的`file_format`参数指定为ONNX即可：`file_format = 'ONNX'`。