From 310a34c177e2d73be4333db15c42a43103798355 Mon Sep 17 00:00:00 2001 From: lvhan028 Date: Thu, 18 Sep 2025 18:39:00 +0800 Subject: [PATCH] bump version to v0.10.1 --- README.md | 2 +- README_zh-CN.md | 2 +- docs/en/get_started/installation.md | 4 ++-- docs/zh_cn/get_started/installation.md | 4 ++-- lmdeploy/version.py | 2 +- 5 files changed, 7 insertions(+), 7 deletions(-) diff --git a/README.md b/README.md index 8bd7fcbc15..d715739d8b 100644 --- a/README.md +++ b/README.md @@ -211,7 +211,7 @@ 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 ``` diff --git a/README_zh-CN.md b/README_zh-CN.md index 7d7635dc70..3328c43f43 100644 --- a/README_zh-CN.md +++ b/README_zh-CN.md @@ -212,7 +212,7 @@ 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 ``` diff --git a/docs/en/get_started/installation.md b/docs/en/get_started/installation.md index f0a9135907..90ed2a8a92 100644 --- a/docs/en/get_started/installation.md +++ b/docs/en/get_started/installation.md @@ -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 ``` @@ -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. diff --git a/docs/zh_cn/get_started/installation.md b/docs/zh_cn/get_started/installation.md index 67b76a88b9..3ec71b0ccd 100644 --- a/docs/zh_cn/get_started/installation.md +++ b/docs/zh_cn/get_started/installation.md @@ -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 ``` @@ -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。 diff --git a/lmdeploy/version.py b/lmdeploy/version.py index 9f36352280..63a6d62d3d 100644 --- a/lmdeploy/version.py +++ b/lmdeploy/version.py @@ -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__