pip3 install paddle-serving-server-gpu==0.6.0.post102 #GPU with CUDA10.2 + TensorRT7
pip3 install paddle-serving-client==0.6.2
pip3 install paddle-serving-server==0.6.2# CPU
pip3 install paddle-serving-app==0.6.2
pip3 install paddle-serving-server-gpu==0.6.2.post102 #GPU with CUDA10.2 + TensorRT7
# DO NOT RUN ALL COMMANDS! check your GPU env and select the right one
pip3 install paddle-serving-server-gpu==0.6.0.post101 # GPU with CUDA10.1 + TensorRT6
pip3 install paddle-serving-server-gpu==0.6.0.post11 # GPU with CUDA10.1 + TensorRT7
pip3 install paddle-serving-server-gpu==0.6.2.post101 # GPU with CUDA10.1 + TensorRT6
pip3 install paddle-serving-server-gpu==0.6.2.post11 # GPU with CUDA10.1 + TensorRT7
```
You may need to use a domestic mirror source (in China, you can use the Tsinghua mirror source, add `-i https://pypi.tuna.tsinghua.edu.cn/simple` to pip command) to speed up the download.
Running Images is lighter than Develop Images, and Running Images are too many due to multiple combinations of python, device environment. If you want to know about it, plese check the document [Paddle Serving on Kubernetes.](PADDLE_SERVING_ON_KUBERNETES.md).
Running Images is lighter than Develop Images, and Running Images are made up with serving whl and bin, but without develop tools like cmake because of lower image size. If you want to know about it, plese check the document [Paddle Serving on Kubernetes.](PADDLE_SERVING_ON_KUBERNETES.md).
**Tips:** If you want to use CPU server and GPU server (version>=0.5.0) at the same time, you should check the gcc version, only Cuda10.1/10.2/11 can run with CPU server owing to the same gcc version(8.2).
