diff --git a/docs/source_en/benchmark.md b/docs/source_en/benchmark.md
index 51fd7faaef4c4e91382a85d00ca102fcc764e04d..6c541a6755ab8ebc991e5be75c745cef167c454e 100644
--- a/docs/source_en/benchmark.md
+++ b/docs/source_en/benchmark.md
@@ -3,7 +3,7 @@
This document describes the MindSpore benchmarks.
-For details about the MindSpore pre-trained model, see [Model Zoo](https://gitee.com/mindspore/mindspore/tree/master/mindspore/model_zoo).
+For details about the MindSpore pre-trained model, see [Model Zoo](https://gitee.com/mindspore/mindspore/tree/master/model_zoo).
## Training Performance
diff --git a/docs/source_en/network_list.md b/docs/source_en/network_list.md
index a5814d1b581288de7652b5ef941791372f0051b6..86987353a42fdf11f40f5d60ed40de042d7fe463 100644
--- a/docs/source_en/network_list.md
+++ b/docs/source_en/network_list.md
@@ -5,11 +5,11 @@
| Domain | Sub Domain | Network | Ascend | GPU | CPU
|:------ |:------| :----------- |:------ |:------ |:-----
|Computer Version (CV) | Image Classification | [AlexNet](https://gitee.com/mindspore/mindspore/blob/master/model_zoo/alexnet/src/alexnet.py) | Supported | Supported | Doing
-| Computer Version (CV) | Image Classification | [GoogleNet](https://gitee.com/mindspore/mindspore/blob/master/mindspore/model_zoo/googlenet.py) | Supported | Doing | Doing
+| Computer Version (CV) | Image Classification | [GoogleNet](https://gitee.com/mindspore/mindspore/blob/master/model_zoo/googlenet/src/googlenet.py) | Supported | Doing | Doing
| Computer Version (CV) | Image Classification | [LeNet](https://gitee.com/mindspore/mindspore/blob/master/model_zoo/lenet/src/lenet.py) | Supported | Supported | Supported
-| Computer Version (CV) | Image Classification | [ResNet-50](https://gitee.com/mindspore/mindspore/blob/master/mindspore/model_zoo/resnet.py) | Supported | Doing | Doing
-|Computer Version (CV) | Image Classification | [ResNet-101](https://gitee.com/mindspore/mindspore/blob/master/mindspore/model_zoo/resnet.py) | Supported |Doing | Doing
-| Computer Version (CV) | Image Classification | [VGG16](https://gitee.com/mindspore/mindspore/blob/master/mindspore/model_zoo/vgg.py) | Supported | Doing | Doing
+| Computer Version (CV) | Image Classification | [ResNet-50](https://gitee.com/mindspore/mindspore/blob/master/model_zoo/resnet/src/resnet.py) | Supported | Doing | Doing
+|Computer Version (CV) | Image Classification | [ResNet-101](https://gitee.com/mindspore/mindspore/blob/master/model_zoo/resnet/src/resnet.py) | Supported |Doing | Doing
+| Computer Version (CV) | Image Classification | [VGG16](https://gitee.com/mindspore/mindspore/blob/master/model_zoo/vgg16/src/vgg.py) | Supported | Doing | Doing
| Computer Version (CV) | Mobile Image Classification
Image Classification
Semantic Tegmentation | [MobileNetV2](https://gitee.com/mindspore/mindspore/blob/master/model_zoo/mobilenetv2/src/mobilenetV2.py) | Supported | Doing | Doing
|Computer Version (CV) | Targets Detection | [SSD](https://gitee.com/mindspore/mindspore/blob/master/model_zoo/ssd/src/ssd.py) | Supported |Doing | Doing
| Computer Version (CV) | Targets Detection | [YoloV3](https://gitee.com/mindspore/mindspore/blob/master/model_zoo/yolov3/src/yolov3.py) | Supported | Doing | Doing
diff --git a/docs/source_zh_cn/benchmark.md b/docs/source_zh_cn/benchmark.md
index 264a5f6d69fa784a8c41f9105eb6035fbf835b2a..4d3f4efcbe1679ff1b5e76f6f277dc3aa76ade0e 100644
--- a/docs/source_zh_cn/benchmark.md
+++ b/docs/source_zh_cn/benchmark.md
@@ -2,7 +2,7 @@
-本文介绍MindSpore的基准性能。MindSpore预训练模型可参考[Model Zoo](https://gitee.com/mindspore/mindspore/tree/master/mindspore/model_zoo)。
+本文介绍MindSpore的基准性能。MindSpore预训练模型可参考[Model Zoo](https://gitee.com/mindspore/mindspore/tree/master/model_zoo)。
## 训练性能
diff --git a/docs/source_zh_cn/network_list.md b/docs/source_zh_cn/network_list.md
index 5b0283f845a761008d52347181be99dd37554429..b972602bda84e282307cdbcbf2003f16b15ae7ab 100644
--- a/docs/source_zh_cn/network_list.md
+++ b/docs/source_zh_cn/network_list.md
@@ -5,11 +5,11 @@
| 领域 | 子领域 | 网络 | Ascend | GPU | CPU
|:------ |:------| :----------- |:------ |:------ |:-----
|计算机视觉（CV） | 图像分类（Image Classification） | [AlexNet](https://gitee.com/mindspore/mindspore/blob/master/model_zoo/alexnet/src/alexnet.py) | Supported | Supported | Doing
-| 计算机视觉（CV） | 图像分类（Image Classification） | [GoogleNet](https://gitee.com/mindspore/mindspore/blob/master/mindspore/model_zoo/googlenet.py) | Supported | Doing | Doing
+| 计算机视觉（CV） | 图像分类（Image Classification） | [GoogleNet](https://gitee.com/mindspore/mindspore/blob/master/model_zoo/googlenet/src/googlenet.py) | Supported | Doing | Doing
| 计算机视觉（CV） | 图像分类（Image Classification） | [LeNet](https://gitee.com/mindspore/mindspore/blob/master/model_zoo/lenet/src/lenet.py) | Supported | Supported | Supported
-| 计算机视觉（CV） | 图像分类（Image Classification） | [ResNet-50](https://gitee.com/mindspore/mindspore/blob/master/mindspore/model_zoo/resnet.py) | Supported | Doing | Doing
-|计算机视觉（CV） | 图像分类（Image Classification） | [ResNet-101](https://gitee.com/mindspore/mindspore/blob/master/mindspore/model_zoo/resnet.py) | Supported |Doing | Doing
-| 计算机视觉（CV） | 图像分类（Image Classification） | [VGG16](https://gitee.com/mindspore/mindspore/blob/master/mindspore/model_zoo/vgg.py) | Supported | Doing | Doing
+| 计算机视觉（CV） | 图像分类（Image Classification） | [ResNet-50](https://gitee.com/mindspore/mindspore/blob/master/model_zoo/resnet/src/resnet.py) | Supported | Doing | Doing
+|计算机视觉（CV） | 图像分类（Image Classification） | [ResNet-101](https://gitee.com/mindspore/mindspore/blob/master/model_zoo/resnet/src/resnet.py) | Supported |Doing | Doing
+| 计算机视觉（CV） | 图像分类（Image Classification） | [VGG16](https://gitee.com/mindspore/mindspore/blob/master/model_zoo/vgg16/src/vgg.py) | Supported | Doing | Doing
| 计算机视觉（CV） | 移动端图像分类（Mobile Image Classification）
目标检测（Image Classification）
语义分割（Semantic Tegmentation） | [MobileNetV2](https://gitee.com/mindspore/mindspore/blob/master/model_zoo/mobilenetv2/src/mobilenetV2.py) | Supported | Doing | Doing
|计算机视觉（CV） | 目标检测（Targets Detection） | [SSD](https://gitee.com/mindspore/mindspore/blob/master/model_zoo/ssd/src/ssd.py) | Supported |Doing | Doing
| 计算机视觉（CV） | 目标检测（Targets Detection） | [YoloV3](https://gitee.com/mindspore/mindspore/blob/master/model_zoo/yolov3/src/yolov3.py) | Supported | Doing | Doing
diff --git a/resource/faq/FAQ_en.md b/resource/faq/FAQ_en.md
index 7fa3b3034787ff8ea08b355864c47e199bc1cfb6..5815ab26b8cfaecc15635dd13bec6e6b1fa6c772 100644
--- a/resource/faq/FAQ_en.md
+++ b/resource/faq/FAQ_en.md
@@ -74,7 +74,7 @@ A: MindSpore has basic support for common training scenarios, please refer to [R
Q: What are the available recommendation or text generation networks or models provided by MindSpore?
-A: Currently, recommendation models such as Wide & Deep, DeepFM, and NCF are under development. In the natural language processing (NLP) field, Bert\_NEZHA is available and models such as MASS are under development. You can rebuild the network into a text generation network based on the scenario requirements. Please stay tuned for updates on the [MindSpore Model Zoo](https://gitee.com/mindspore/mindspore/tree/master/mindspore/model_zoo).
+A: Currently, recommendation models such as Wide & Deep, DeepFM, and NCF are under development. In the natural language processing (NLP) field, Bert\_NEZHA is available and models such as MASS are under development. You can rebuild the network into a text generation network based on the scenario requirements. Please stay tuned for updates on the [MindSpore Model Zoo](https://gitee.com/mindspore/mindspore/tree/master/model_zoo).
### Backend Support
diff --git a/resource/faq/FAQ_zh_cn.md b/resource/faq/FAQ_zh_cn.md
index db448da184e2b5370da5245b4992fa995be8aa38..3ee10f6b70d94b00af22bc113e9b98e5e40f8248 100644
--- a/resource/faq/FAQ_zh_cn.md
+++ b/resource/faq/FAQ_zh_cn.md
@@ -73,7 +73,7 @@ A：MindSpore针对典型场景均有模型训练支持，支持情况详见[Rel
Q：MindSpore有哪些现成的推荐类或生成类网络或模型可用？
-A：目前正在开发Wide & Deep、DeepFM、NCF等推荐类模型，NLP领域已经支持Bert_NEZHA，正在开发MASS等模型，用户可根据场景需要改造为生成类网络，可以关注[MindSpore Model Zoo](https://gitee.com/mindspore/mindspore/tree/master/mindspore/model_zoo)。
+A：目前正在开发Wide & Deep、DeepFM、NCF等推荐类模型，NLP领域已经支持Bert_NEZHA，正在开发MASS等模型，用户可根据场景需要改造为生成类网络，可以关注[MindSpore Model Zoo](https://gitee.com/mindspore/mindspore/tree/master/model_zoo)。
### 后端支持
diff --git a/tutorials/source_en/advanced_use/network_migration.md b/tutorials/source_en/advanced_use/network_migration.md
index 70fab25c04fa994d30aa02c7ccf45a1a72669f21..9f396fe5480fbc544b0baf578da8103cb0385450 100644
--- a/tutorials/source_en/advanced_use/network_migration.md
+++ b/tutorials/source_en/advanced_use/network_migration.md
@@ -79,7 +79,7 @@ The ResNet-50 network migration and training on the Ascend 910 is used as an exa
num_shards=device_num, shard_id=rank_id)
```
- Then, perform data augmentation, data cleaning, and batch processing. For details about the code, see .
+ Then, perform data augmentation, data cleaning, and batch processing. For details about the code, see .
3. Build a network.
@@ -214,7 +214,7 @@ The ResNet-50 network migration and training on the Ascend 910 is used as an exa
6. Build the entire network.
- The [ResNet-50](https://gitee.com/mindspore/mindspore/blob/master/mindspore/model_zoo/resnet.py) network structure is formed by connecting multiple defined subnets. Follow the rule of defining subnets before using them and define all the subnets used in the `__init__` and connect subnets in the `construct`.
+ The [ResNet-50](https://gitee.com/mindspore/mindspore/blob/master/model_zoo/resnet/src/resnet.py) network structure is formed by connecting multiple defined subnets. Follow the rule of defining subnets before using them and define all the subnets used in the `__init__` and connect subnets in the `construct`.
7. Define a loss function and an optimizer.
@@ -272,9 +272,7 @@ Models trained on the Ascend 910 AI processor can be used for inference on diffe
## Examples
-1. [Common network script examples](https://gitee.com/mindspore/mindspore/tree/master/example)
+1. [Common dataset examples](https://www.mindspore.cn/tutorial/en/master/use/data_preparation/loading_the_datasets.html)
-2. [Common dataset examples](https://www.mindspore.cn/tutorial/en/master/use/data_preparation/loading_the_datasets.html)
-
-3. [Model Zoo](https://gitee.com/mindspore/mindspore/tree/master/mindspore/model_zoo)
+2. [Model Zoo](https://gitee.com/mindspore/mindspore/tree/master/model_zoo)
diff --git a/tutorials/source_en/use/multi_platform_inference.md b/tutorials/source_en/use/multi_platform_inference.md
index 230af0e3e0cdd929127e1f1bab2b8f7b9b080701..373dc9b634b7ce3a531d58d77582c12f88a10326 100644
--- a/tutorials/source_en/use/multi_platform_inference.md
+++ b/tutorials/source_en/use/multi_platform_inference.md
@@ -16,7 +16,7 @@ Models based on MindSpore training can be used for inference on different hardwa
1. Inference on the Ascend 910 AI processor
- MindSpore provides the `model.eval` API for model validation. You only need to import the validation dataset. The processing method of the validation dataset is the same as that of the training dataset. For details about the complete code, see .
+ MindSpore provides the `model.eval` API for model validation. You only need to import the validation dataset. The processing method of the validation dataset is the same as that of the training dataset. For details about the complete code, see .
```python
res = model.eval(dataset)
diff --git a/tutorials/source_zh_cn/advanced_use/network_migration.md b/tutorials/source_zh_cn/advanced_use/network_migration.md
index 3e9cf2e776d0ffc163e2cb8dd83da375bfd4d752..8d3f574dbe4a90fec2c34772db6d2cdd12426fba 100644
--- a/tutorials/source_zh_cn/advanced_use/network_migration.md
+++ b/tutorials/source_zh_cn/advanced_use/network_migration.md
@@ -77,7 +77,7 @@ MindSpore与TensorFlow、PyTorch在网络结构组织方式上，存在一定差
num_shards=device_num, shard_id=rank_id)
```
- 然后对数据进行了数据增强、数据清洗和批处理等操作。代码详见。
+ 然后对数据进行了数据增强、数据清洗和批处理等操作。代码详见。
3. 构建网络。
@@ -210,7 +210,7 @@ MindSpore与TensorFlow、PyTorch在网络结构组织方式上，存在一定差
6. 构造整网。
- 将定义好的多个子网连接起来就是整个[ResNet-50](https://gitee.com/mindspore/mindspore/blob/master/mindspore/model_zoo/resnet.py)网络的结构了。同样遵循先定义后使用的原则，在`__init__`中定义所有用到的子网，在`construct`中连接子网。
+ 将定义好的多个子网连接起来就是整个[ResNet-50](https://gitee.com/mindspore/mindspore/blob/master/model_zoo/resnet/src/resnet.py)网络的结构了。同样遵循先定义后使用的原则，在`__init__`中定义所有用到的子网，在`construct`中连接子网。
7. 定义损失函数和优化器。
@@ -267,8 +267,6 @@ MindSpore与TensorFlow、PyTorch在网络结构组织方式上，存在一定差
## 样例参考
-1. [常用网络脚本样例](https://gitee.com/mindspore/mindspore/tree/master/example)
+1. [常用数据集读取样例](https://www.mindspore.cn/tutorial/zh-CN/master/use/data_preparation/loading_the_datasets.html)
-2. [常用数据集读取样例](https://www.mindspore.cn/tutorial/zh-CN/master/use/data_preparation/loading_the_datasets.html)
-
-3. [Model Zoo](https://gitee.com/mindspore/mindspore/tree/master/mindspore/model_zoo)
\ No newline at end of file
+2. [Model Zoo](https://gitee.com/mindspore/mindspore/tree/master/model_zoo)
\ No newline at end of file