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.
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)
- 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`).
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.
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.
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
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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)
