Install the service whl package. There are three types of client, app and server. The server is divided into CPU and GPU. Choose one installation according to the environment.
- GPU with CUDA10.2 + Cudnn7 + TensorRT6(Recommended)
By default, the domestic Tsinghua mirror source is turned on to speed up the download. If you use a proxy, you can turn it off（`-i https://pypi.tuna.tsinghua.edu.cn/simple`).
If you need to use the installation package compiled by the develop branch, please download the download address from [Latest installation package list](./Latest_Packages_CN.md), and use the `pip install` command to install. If you want to compile by yourself, please refer to [Paddle Serving Compilation Document](./Compile_CN.md).
If you need to use the installation package compiled by the develop branch, please download the download address from [Download wheel packages](./Latest_Packages_EN.md), and use the `pip install` command to install. If you want to compile by yourself, please refer to [Paddle Serving Compilation Document](./Compile_CN.md).
The paddle-serving-server and paddle-serving-server-gpu installation packages support Centos 6/7, Ubuntu 16/18 and Windows 10.
for most users, we do not need to read this section. But if you deploy your Paddle Serving on a machine without network, you will encounter a problem that the binary executable tar file cannot be downloaded. Therefore, here we give you all the download links for various environment.
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@@ -27,15 +27,16 @@ for most users, we do not need to read this section. But if you deploy your Padd
Check the following table, and copy the address of hyperlink then run `pip3 install`. For example, if you want to install `paddle-serving-server-0.0.0-py3-non-any.whl`, right click the hyper link and copy the link address, the final command is `pip3 install https://paddle-serving.bj.bcebos.com/test-dev/whl/paddle_serving_server-0.0.0-py3-none-any.whl`.
| | develop whl | develop bin | stable whl | stable bin |
for most users, we do not need to read this section. But if you deploy your Paddle Serving on a machine without network, you will encounter a problem that the binary executable tar file cannot be downloaded. Therefore, here we give you all the download links for various environment.
### How to setup SERVING_BIN offline?
- download the serving server whl package and bin package, and make sure they are for the same environment
- download the serving client whl and serving app whl, pay attention to the Python version.
-`pip install ` the serving and `tar xf ` the binary package, then `export SERVING_BIN=$PWD/serving-gpu-cuda11-0.0.0/serving` (take Cuda 11 as the example)
for kunlun user who uses arm-xpu or x86-xpu can download the wheel packages as follows. Users should use the xpu-beta docker [DOCKER IMAGES](./Docker_Images_CN.md)
