diff --git a/README.md b/README.md
index 31bbe824b3bcf6fef9cbf9df6a57ad6166be7bf3..6027d1fd5b32fee64ffd1a67442f08fd7c50499e 100644
--- a/README.md
+++ b/README.md
@@ -33,7 +33,7 @@ We consider deploying deep learning inference service online to be a user-facing
 
 - Any model trained by [PaddlePaddle](https://github.com/paddlepaddle/paddle) can be directly used or [Model Conversion Interface](./doc/SAVE_CN.md) for online deployment of Paddle Serving.
 - Support [Multi-model Pipeline Deployment](./doc/PIPELINE_SERVING.md), and provide the requirements of the REST interface and RPC interface itself, [Pipeline example](./python/examples/pipeline).
-- Support the major model libraries of the Paddle ecosystem, such as [PaddleDetection](./python/examples/detection), [PaddleOCR](./python/examples/ocr), [PaddleRec](https://github.com/PaddlePaddle/PaddleRec/tree/master/tools/recserving/movie_recommender).
+- Support the model zoos from the Paddle ecosystem, such as [PaddleDetection](./python/examples/detection), [PaddleOCR](./python/examples/ocr), [PaddleRec](https://github.com/PaddlePaddle/PaddleRec/tree/master/tools/recserving/movie_recommender).
 - Provide a variety of pre-processing and post-processing to facilitate users in training, deployment and other stages of related code, bridging the gap between AI developers and application developers, please refer to
 [Serving Examples](./python/examples/).
 
@@ -118,6 +118,16 @@ pip install paddlepaddle==2.0.0
 pip install paddlepaddle-gpu==2.0.0
 ```
 
+**Note**: If your Cuda version is not 10.2, please do not execute the above commands directly, you need to refer to [Paddle official documentation-multi-version whl package list
+](https://www.paddlepaddle.org.cn/documentation/docs/en/install/Tables_en.html#multi-version-whl-package-list-release)
+
+Select the url link of the corresponding GPU environment and install it. For example, for Python2.7 users of Cuda 9.0, please select `cp27-cp27mu` and
+The url corresponding to `cuda9.0_cudnn7-mkl`, copy it and run
+```
+pip install https://paddle-wheel.bj.bcebos.com/2.0.0-gpu-cuda9-cudnn7-mkl/paddlepaddle_gpu-2.0.0.post90-cp27-cp27mu-linux_x86_64.whl
+```
+If it is other environment and Python version, please find the corresponding link in the table and install it with pip.
+
 For **Windows Users**, please read the document [Paddle Serving for Windows Users](./doc/WINDOWS_TUTORIAL.md)
 
 <h2 align="center">Quick Start Example</h2>
diff --git a/doc/DESIGN_DOC.md b/doc/DESIGN_DOC.md
index 6f9718574bac9c2089e57ede68d8ee975af81523..d0c66a97946f700690097e1cb82d589476735edc 100644
--- a/doc/DESIGN_DOC.md
+++ b/doc/DESIGN_DOC.md
@@ -70,7 +70,7 @@ The inference framework of the well-known deep learning platform only supports C
 
 > Model conversion across deep learning platforms
 
-Models trained on other deep learning platforms can be passed《[PaddlePaddle/X2Paddle工具](https://github.com/PaddlePaddle/X2Paddle)》.We convert multiple mainstream CV models to Paddle models. TensorFlow, Caffe, ONNX, PyTorch model conversion is tested.《[An End-to-end Tutorial from Training to Inference Service Deployment](TRAIN_TO_SERVICE.md)
+Models trained on other deep learning platforms can be passed《[PaddlePaddle/X2Paddle工具](https://github.com/PaddlePaddle/X2Paddle)》.We convert multiple mainstream CV models to Paddle models. TensorFlow, Caffe, ONNX, PyTorch model conversion is tested.《[An End-to-end Tutorial from Training to Inference Service Deployment](TRAIN_TO_SERVICE.md)》
 
 Because it is impossible to directly view the feed and fetch parameter information in the model file, it is not convenient for users to assemble the parameters. Therefore, Paddle Serving developed a tool to convert the Paddle model into Serving format and generate a prototxt file containing feed and fetch parameter information. The following figure is the generated prototxt file of the uci_housing example. For more conversion methods, refer to the document《[How to save a servable model of Paddle Serving?](SAVE.md)》.
 ```