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Update version in docs

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Jiang-Jia-Jun
2025-09-02 19:21:10 +08:00
parent 8e1b35a09b
commit 18e5d355a1
4 changed files with 8 additions and 8 deletions
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6
docs/get_started/installation/kunlunxin_xpu.md
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@@ -25,9 +25,9 @@ Verified platform:
```bash
mkdir Work
cd Work
docker pull ccr-2vdh3abv-pub.cnc.bj.baidubce.com/paddlepaddle/fastdeploy-xpu:2.1.0
docker pull ccr-2vdh3abv-pub.cnc.bj.baidubce.com/paddlepaddle/fastdeploy-xpu:2.1.1
docker run --name fastdeploy-xpu --net=host -itd --privileged -v $PWD:/Work -w /Work \
ccr-2vdh3abv-pub.cnc.bj.baidubce.com/paddlepaddle/fastdeploy-xpu:2.1.0 \
ccr-2vdh3abv-pub.cnc.bj.baidubce.com/paddlepaddle/fastdeploy-xpu:2.1.1 \
/bin/bash
docker exec -it fastdeploy-xpu /bin/bash
```
@@ -49,7 +49,7 @@ python -m pip install --pre paddlepaddle-xpu -i https://www.paddlepaddle.org.cn/
### Install FastDeploy (**Do NOT install via PyPI source**)
```bash
python -m pip install fastdeploy-xpu==2.1.0 -i https://www.paddlepaddle.org.cn/packages/stable/fastdeploy-xpu-p800/ --extra-index-url https://mirrors.tuna.tsinghua.edu.cn/pypi/web/simple
python -m pip install fastdeploy-xpu==2.1.1 -i https://www.paddlepaddle.org.cn/packages/stable/fastdeploy-xpu-p800/ --extra-index-url https://mirrors.tuna.tsinghua.edu.cn/pypi/web/simple
```
Alternatively, you can install the latest version of FastDeploy (Not recommended)

2
docs/get_started/installation/nvidia_gpu.md
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@@ -13,7 +13,7 @@ The following installation methods are available when your environment meets the
**Notice**: The pre-built image only supports SM80/90 GPU(e.g. H800/A800)，if you are deploying on SM86/89GPU(L40/4090/L20), please reinstall ```fastdpeloy-gpu``` after you create the container.
```shell
docker pull ccr-2vdh3abv-pub.cnc.bj.baidubce.com/paddlepaddle/fastdeploy-cuda-12.6:2.1.0
docker pull ccr-2vdh3abv-pub.cnc.bj.baidubce.com/paddlepaddle/fastdeploy-cuda-12.6:2.1.1
```
## 2. Pre-built Pip Installation

6
docs/zh/get_started/installation/kunlunxin_xpu.md
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@@ -25,9 +25,9 @@
```bash
mkdir Work
cd Work
docker pull ccr-2vdh3abv-pub.cnc.bj.baidubce.com/paddlepaddle/fastdeploy-xpu:2.1.0
docker pull ccr-2vdh3abv-pub.cnc.bj.baidubce.com/paddlepaddle/fastdeploy-xpu:2.1.1
docker run --name fastdeploy-xpu --net=host -itd --privileged -v $PWD:/Work -w /Work \
ccr-2vdh3abv-pub.cnc.bj.baidubce.com/paddlepaddle/fastdeploy-xpu:2.1.0 \
ccr-2vdh3abv-pub.cnc.bj.baidubce.com/paddlepaddle/fastdeploy-xpu:2.1.1 \
/bin/bash
docker exec -it fastdeploy-xpu /bin/bash
```
@@ -49,7 +49,7 @@ python -m pip install --pre paddlepaddle-xpu -i https://www.paddlepaddle.org.cn/
### 安装 FastDeploy（**注意不要通过 pypi 源安装**）
```bash
python -m pip install fastdeploy-xpu==2.1.0 -i https://www.paddlepaddle.org.cn/packages/stable/fastdeploy-xpu-p800/ --extra-index-url https://mirrors.tuna.tsinghua.edu.cn/pypi/web/simple
python -m pip install fastdeploy-xpu==2.1.1 -i https://www.paddlepaddle.org.cn/packages/stable/fastdeploy-xpu-p800/ --extra-index-url https://mirrors.tuna.tsinghua.edu.cn/pypi/web/simple
```
或者你也可以安装最新版 FastDeploy（不推荐）

2
docs/zh/get_started/installation/nvidia_gpu.md
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@@ -15,7 +15,7 @@
**注意**： 如下镜像仅支持SM 80/90架构GPU（A800/H800等），如果你是在L20/L40/4090等SM 86/69架构的GPU上部署，请在创建容器后，卸载```fastdeploy-gpu```再重新安装如下文档指定支持86/89架构的`fastdeploy-gpu`包。
``` shell
docker pull ccr-2vdh3abv-pub.cnc.bj.baidubce.com/paddlepaddle/fastdeploy-cuda-12.6:2.1.0
docker pull ccr-2vdh3abv-pub.cnc.bj.baidubce.com/paddlepaddle/fastdeploy-cuda-12.6:2.1.1
```
## 2. 预编译Pip安装