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Merged
lvhan028 merged 3 commits into from
Sep 26, 2025
Merged

bump version to v0.10.1 #3989

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310a34c
bump version to v0.10.1
lvhan028 Sep 18, 2025
91211e8
Merge branch 'main' into bump-version
lvhan028 Sep 19, 2025
85f5edf
Merge branch 'main' into bump-version
lvhan028 Sep 19, 2025
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2 changes: 1 addition & 1 deletion README.md
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Expand Up @@ -212,7 +212,7 @@ The default prebuilt package is compiled on **CUDA 12** since v0.3.0.
For the GeForce RTX 50 series, please install the LMDeploy prebuilt package complied with **CUDA 12.8**

```shell
export LMDEPLOY_VERSION=0.10.0
export LMDEPLOY_VERSION=0.10.1
export PYTHON_VERSION=310
pip install https://github.com/InternLM/lmdeploy/releases/download/v${LMDEPLOY_VERSION}/lmdeploy-${LMDEPLOY_VERSION}+cu128-cp${PYTHON_VERSION}-cp${PYTHON_VERSION}-manylinux2014_x86_64.whl --extra-index-url https://download.pytorch.org/whl/cu128
```
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2 changes: 1 addition & 1 deletion README_zh-CN.md
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Expand Up @@ -213,7 +213,7 @@ pip install lmdeploy
若使用 GeForce RTX 50 系列显卡，请安装基于 **CUDA 12.8** 编译的 LMDeploy 预编译包。

```shell
export LMDEPLOY_VERSION=0.10.0
export LMDEPLOY_VERSION=0.10.1
export PYTHON_VERSION=310
pip install https://github.com/InternLM/lmdeploy/releases/download/v${LMDEPLOY_VERSION}/lmdeploy-${LMDEPLOY_VERSION}+cu128-cp${PYTHON_VERSION}-cp${PYTHON_VERSION}-manylinux2014_x86_64.whl --extra-index-url https://download.pytorch.org/whl/cu128
```
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4 changes: 2 additions & 2 deletions docs/en/get_started/installation.md
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Expand Up @@ -23,7 +23,7 @@ pip install lmdeploy
The default prebuilt package is compiled on **CUDA 12**. If CUDA 11+ (>=11.3) is required, you can install lmdeploy by:

```shell
export LMDEPLOY_VERSION=0.10.0
export LMDEPLOY_VERSION=0.10.1
export PYTHON_VERSION=310
pip install https://github.com/InternLM/lmdeploy/releases/download/v${LMDEPLOY_VERSION}/lmdeploy-${LMDEPLOY_VERSION}+cu118-cp${PYTHON_VERSION}-cp${PYTHON_VERSION}-manylinux2014_x86_64.whl --extra-index-url https://download.pytorch.org/whl/cu118
```
Expand Down Expand Up @@ -51,7 +51,7 @@ DISABLE_TURBOMIND=1 pip install git+https://github.com/InternLM/lmdeploy.git
If you prefer a specific version instead of the `main` branch of LMDeploy, you can specify it in your command:

```shell
pip install https://github.com/InternLM/lmdeploy/archive/refs/tags/v0.10.0.zip
pip install https://github.com/InternLM/lmdeploy/archive/refs/tags/v0.10.1.zip
```

If you want to build LMDeploy with support for Ascend, Cambricon, or MACA, install LMDeploy with the corresponding `LMDEPLOY_TARGET_DEVICE` environment variable.
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4 changes: 2 additions & 2 deletions docs/zh_cn/get_started/installation.md
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Expand Up @@ -23,7 +23,7 @@ pip install lmdeploy
默认的预构建包是在 **CUDA 12** 上编译的。如果需要 CUDA 11+ (>=11.3)，你可以使用以下命令安装 lmdeploy：

```shell
export LMDEPLOY_VERSION=0.10.0
export LMDEPLOY_VERSION=0.10.1
export PYTHON_VERSION=310
pip install https://github.com/InternLM/lmdeploy/releases/download/v${LMDEPLOY_VERSION}/lmdeploy-${LMDEPLOY_VERSION}+cu118-cp${PYTHON_VERSION}-cp${PYTHON_VERSION}-manylinux2014_x86_64.whl --extra-index-url https://download.pytorch.org/whl/cu118
```
Expand Down Expand Up @@ -51,7 +51,7 @@ DISABLE_TURBOMIND=1 pip install git+https://github.com/InternLM/lmdeploy.git
如果您希望使用特定版本，而不是 LMDeploy 的 `main` 分支，可以在命令行中指定：

```shell
pip install https://github.com/InternLM/lmdeploy/archive/refs/tags/v0.10.0.zip
pip install https://github.com/InternLM/lmdeploy/archive/refs/tags/v0.10.1.zip
```

如果您希望构建支持昇腾、寒武纪或沐熙的 LMDeploy，请使用相应的 `LMDEPLOY_TARGET_DEVICE` 环境变量进行安装。
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2 changes: 1 addition & 1 deletion lmdeploy/version.py
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@@ -1,7 +1,7 @@
# Copyright (c) OpenMMLab. All rights reserved.
from typing import Tuple

__version__ = '0.10.0'
__version__ = '0.10.1'
short_version = __version__


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