diff --git a/README.md b/README.md
index cc2424b5406d72d489e98c9f6bd979013bb94002..466ee1d58cd6834dc63f38fc59a58849cb837357 100644
--- a/README.md
+++ b/README.md
@@ -1,100 +1,32 @@
-
-[](https://pypi.org/project/mindspore)
-[](https://badge.fury.io/py/mindspore)
-[](https://pepy.tech/project/mindspore)
-[](https://hub.docker.com/r/mindspore/mindspore-cpu)
-[](https://github.com/mindspore-ai/mindspore/blob/master/LICENSE)
-[](https://gitee.com/mindspore/mindspore/pulls)
-[查看中文](./README_CN.md)
+MindSpore 是一个开源的深度学习训练/推理框架，可用于移动、边缘和云场景。MindSpore 旨在为数据科学家和算法工程师提供友好的设计和高效的执行，并支持 Ascend AI 处理器及软硬件协同优化。作为一个全球性的 AI 开源社区，MindSpore 也致力于推动 AI 软硬件生态系统的丰富与发展。
-
+## 特性
-- [What Is MindSpore](#what-is-mindspore)
- - [Automatic Differentiation](#automatic-differentiation)
- - [Automatic Parallel](#automatic-parallel)
-- [Installation](#installation)
- - [Pip mode method installation](#pip-mode-method-installation)
- - [Source code compilation installation](#source-code-compilation-installation)
- - [Docker Image](#docker-image)
-- [Quickstart](#quickstart)
-- [Docs](#docs)
-- [Community](#community)
- - [Governance](#governance)
- - [Communication](#communication)
-- [Contributing](#contributing)
-- [Maintenance phases](#maintenance-phases)
-- [Maintenance status](#maintenance-status)
-- [Release Notes](#release-notes)
-- [License](#license)
+### 自动微分
-
+MindSpore 的自动微分基于源码转换（Source Transformation），与操作符重载（Operator Overloading）相比，支持控制流的自动微分，可以在编译阶段进行优化，从而实现卓越的性能。详情请参考 [自动微分文档](https://gitee.com/mindspore/docs)。
-## What Is MindSpore
+### 自动并行
-MindSpore is a new open source deep learning training/inference framework that
-could be used for mobile, edge and cloud scenarios. MindSpore is designed to
-provide development experience with friendly design and efficient execution for
-the data scientists and algorithmic engineers, native support for Ascend AI
-processor, and software hardware co-optimization. At the meantime MindSpore as
-a global AI open source community, aims to further advance the development and
-enrichment of the AI software/hardware application ecosystem.
+MindSpore 支持数据并行、模型并行和混合并行，并能自动选择最低成本的模型拆分策略，实现高效的分布式训练。更多详情请参考 [自动并行文档](https://gitee.com/mindspore/docs)。
-
+## 安装
-For more details please check out our [Architecture Guide](https://www.mindspore.cn/tutorials/en/master/beginner/introduction.html).
+MindSpore 支持多种后端和操作系统，安装方式包括 pip 安装、源码编译安装和 Docker 镜像安装。
-### Automatic Differentiation
+### 使用 pip 安装
-Currently, there are two automatic differentiation techniques in mainstream deep learning frameworks:
+以 CPU 和 Ubuntu-x86 平台为例，安装步骤如下：
-- **Operator Overloading (OO)**: Overloading the basic operators of the programming language to encapsulate their gradient rules. Record the operation trajectory of the network during forward execution in an operator overloaded manner, then apply the chain rule to the dynamically generated data flow graph to implement automatic differentiation.
-- **Source Transformation (ST)**: This technology is evolving from the functional programming framework and performs automatic differential transformation on the intermediate expression (the expression form of the program during the compilation process) in the form of just-in-time compilation (JIT), supporting complex control flow scenarios, higher-order functions and closures.
-
-PyTorch used OO. Compared to ST, OO generates gradient graph in runtime, so it does not need to take function call and control flow into consideration, which makes it easier to develop. However, OO can not perform gradient graph optimization in compilation time and the control flow has to be unfolded in runtime, so it is difficult to achieve extreme optimization in performance.
-
-MindSpore implemented automatic differentiation based on ST. On the one hand, it supports automatic differentiation of automatic control flow, so it is quite convenient to build models like PyTorch. On the other hand, MindSpore can perform static compilation optimization on neural networks to achieve great performance.
-
-
-
-The implementation of MindSpore automatic differentiation can be understood as the symbolic differentiation of the program itself. Because MindSpore IR is a functional intermediate expression, it has an intuitive correspondence with the composite function in basic algebra. The derivation formula of the composite function composed of arbitrary basic functions can be derived. Each primitive operation in MindSpore IR can correspond to the basic functions in basic algebra, which can build more complex flow control.
-
-### Automatic Parallel
-
-The goal of MindSpore automatic parallel is to build a training method that combines data parallelism, model parallelism, and hybrid parallelism. It can automatically select a least cost model splitting strategy to achieve automatic distributed parallel training.
-
-
-
-At present, MindSpore uses a fine-grained parallel strategy of splitting operators, that is, each operator in the figure is split into a cluster to complete parallel operations. The splitting strategy during this period may be very complicated, but as a developer advocating Pythonic, you don't need to care about the underlying implementation, as long as the top-level API compute is efficient.
-
-## Installation
-
-### Pip mode method installation
-
-MindSpore offers build options across multiple backends:
-
-| Hardware Platform | Operating System | Status |
-| :---------------- | :--------------- | :----- |
-| Ascend | Ubuntu-x86 | ✔️ |
-| | Ubuntu-aarch64 | ✔️ |
-| | EulerOS-aarch64 | ✔️ |
-| | CentOS-x86 | ✔️ |
-| | CentOS-aarch64 | ✔️ |
-| GPU CUDA 10.1 | Ubuntu-x86 | ✔️ |
-| CPU | Ubuntu-x86 | ✔️ |
-| | Ubuntu-aarch64 | ✔️ |
-| | Windows-x86 | ✔️ |
-
-For installation using `pip`, take `CPU` and `Ubuntu-x86` build version as an example:
-
-1. Download whl from [MindSpore download page](https://www.mindspore.cn/versions/en), and install the package.
+1. 从 [MindSpore 官网下载页面](https://www.mindspore.cn/versions/en) 下载对应的 whl 包并安装。
```bash
pip install https://ms-release.obs.cn-north-4.myhuaweicloud.com/1.2.0-rc1/MindSpore/cpu/ubuntu_x86/mindspore-1.2.0rc1-cp37-cp37m-linux_x86_64.whl
```
-2. Run the following command to verify the install.
+2. 验证安装：
```python
import numpy as np
@@ -120,194 +52,59 @@ For installation using `pip`, take `CPU` and `Ubuntu-x86` build version as an ex
print(mul(x, y))
```
- ```text
- [ 4. 10. 18.]
- ```
+### 使用 Docker 镜像安装
-Use pip mode method to install MindSpore in different environments. Refer to the following documents.
+MindSpore 提供了 CPU 和 GPU 的 Docker 镜像，可直接从 [Docker Hub](https://hub.docker.com/r/mindspore) 拉取并运行。
-- [Using pip mode method to install MindSpore in Ascend environment](https://gitee.com/mindspore/docs/blob/master/install/mindspore_ascend_install_pip_en.md)
-- [Using pip mode method to install MindSpore in GPU environment](https://gitee.com/mindspore/docs/blob/master/install/mindspore_gpu_install_pip_en.md)
-- [Using pip mode method to install MindSpore in CPU environment](https://gitee.com/mindspore/docs/blob/master/install/mindspore_cpu_install_pip_en.md)
-
-### Source code compilation installation
-
-Use the source code compilation method to install MindSpore in different environments. Refer to the following documents.
-
-- [Using the source code compilation method to install MindSpore in Ascend environment](https://gitee.com/mindspore/docs/blob/master/install/mindspore_ascend_install_source_en.md)
-- [Using the source code compilation method to install MindSpore in GPU environment](https://gitee.com/mindspore/docs/blob/master/install/mindspore_gpu_install_source_en.md)
-- [Using the source code compilation method to install MindSpore in CPU environment](https://gitee.com/mindspore/docs/blob/master/install/mindspore_cpu_install_source_en.md)
-
-### Docker Image
-
-MindSpore docker image is hosted on [Docker Hub](https://hub.docker.com/r/mindspore),
-currently the containerized build options are supported as follows:
-
-| Hardware Platform | Docker Image Repository | Tag | Description |
-| :---------------- | :---------------------- | :-- | :---------- |
-| CPU | `mindspore/mindspore-cpu` | `x.y.z` | Production environment with pre-installed MindSpore `x.y.z` CPU release. |
-| | | `devel` | Development environment provided to build MindSpore (with `CPU` backend) from the source, refer to for installation details. |
-| | | `runtime` | Runtime environment provided to install MindSpore binary package with `CPU` backend. |
-| GPU | `mindspore/mindspore-gpu` | `x.y.z` | Production environment with pre-installed MindSpore `x.y.z` GPU release. |
-| | | `devel` | Development environment provided to build MindSpore (with `GPU CUDA10.1` backend) from the source, refer to for installation details. |
-| | | `runtime` | Runtime environment provided to install MindSpore binary package with `GPU CUDA10.1` backend. |
-
-> **NOTICE:** For GPU `devel` docker image, it's NOT suggested to directly install the whl package after building from the source, instead we strongly RECOMMEND you transfer and install the whl package inside GPU `runtime` docker image.
-
-- CPU
-
- For `CPU` backend, you can directly pull and run the latest stable image using the below command:
+- **CPU 示例：**
```bash
docker pull mindspore/mindspore-cpu:1.1.0
docker run -it mindspore/mindspore-cpu:1.1.0 /bin/bash
```
-- GPU
-
- For `GPU` backend, please make sure the `nvidia-container-toolkit` has been installed in advance, here are some install guidelines for `Ubuntu` users:
-
- ```bash
- DISTRIBUTION=$(. /etc/os-release; echo $ID$VERSION_ID)
- curl -s -L https://nvidia.github.io/nvidia-docker/gpgkey | apt-key add -
- curl -s -L https://nvidia.github.io/nvidia-docker/$DISTRIBUTION/nvidia-docker.list | tee /etc/apt/sources.list.d/nvidia-docker.list
-
- sudo apt-get update && sudo apt-get install -y nvidia-container-toolkit nvidia-docker2
- sudo systemctl restart docker
- ```
-
- Then edit the file daemon.json:
-
- ```bash
- $ vim /etc/docker/daemon.json
- {
- "runtimes": {
- "nvidia": {
- "path": "nvidia-container-runtime",
- "runtimeArgs": []
- }
- }
- }
- ```
-
- Restart docker again:
-
- ```bash
- sudo systemctl daemon-reload
- sudo systemctl restart docker
- ```
-
- Then you can pull and run the latest stable image using the below command:
+- **GPU 示例：**
```bash
docker pull mindspore/mindspore-gpu:1.1.0
docker run -it -v /dev/shm:/dev/shm --runtime=nvidia --privileged=true mindspore/mindspore-gpu:1.1.0 /bin/bash
```
- To test if the docker image works, please execute the python code below and check the output:
-
- ```python
- import numpy as np
- import mindspore.context as context
- from mindspore import Tensor
- from mindspore.ops import functional as F
-
- context.set_context(mode=context.PYNATIVE_MODE, device_target="GPU")
-
- x = Tensor(np.ones([1,3,3,4]).astype(np.float32))
- y = Tensor(np.ones([1,3,3,4]).astype(np.float32))
- print(F.tensor_add(x, y))
- ```
-
- ```text
- [[[ 2. 2. 2. 2.],
- [ 2. 2. 2. 2.],
- [ 2. 2. 2. 2.]],
-
- [[ 2. 2. 2. 2.],
- [ 2. 2. 2. 2.],
- [ 2. 2. 2. 2.]],
-
- [[ 2. 2. 2. 2.],
- [ 2. 2. 2. 2.],
- [ 2. 2. 2. 2.]]]
- ```
-
-If you want to learn more about the building process of MindSpore docker images,
-please check out [docker](https://gitee.com/mindspore/mindspore/blob/master/scripts/docker/README.md) repo for the details.
-
-## Quickstart
-
-See the [Quick Start](https://www.mindspore.cn/tutorials/en/master/beginner/quick_start.html)
-to implement the image classification.
-
-## Docs
-
-More details about installation guide, tutorials and APIs, please see the
-[User Documentation](https://gitee.com/mindspore/docs).
-
-## Community
-
-### Governance
+## 快速入门
-Check out how MindSpore Open Governance [works](https://gitee.com/mindspore/community/blob/master/governance.md).
+有关如何实现图像分类任务，请参考 [MindSpore 快速入门教程](https://www.mindspore.cn/tutorials/zh-CN/master/beginner/quick_start.html)。
-### Communication
+## 文档
-- IRC channel at `#mindspore` (only for meeting minutes logging purpose)
-- Video Conferencing: TBD
-- Mailing-list:
+更多安装指南、使用教程和 API 文档，请访问 [MindSpore 官方文档](https://www.mindspore.cn/docs/zh-CN/master/index.html)。
-## Contributing
+## 社区
-Welcome contributions. See our [Contributor Wiki](https://gitee.com/mindspore/mindspore/blob/master/CONTRIBUTING.md) for
-more details.
+MindSpore 作为一个开源社区，欢迎所有参与和贡献。更多信息请参考 [社区治理文档](https://gitee.com/mindspore/community/blob/master/governance.md) 和 [邮件列表](https://mailweb.mindspore.cn/postorius/lists)。
-## Maintenance phases
+## 贡献指南
-Project stable branches will be in one of the following states:
+欢迎贡献代码和文档。详情请参见 [贡献者指南](https://gitee.com/mindspore/mindspore/blob/master/CONTRIBUTING.md)。
-| **State** | **Time frame** | **Summary** |
-|-------------|---------------|--------------------------------------------------|
-| Planning | 1 - 3 months | Features are under planning. |
-| Development | 3 months | Features are under development. |
-| Maintained | 6 - 12 months | All bugfixes are appropriate. Releases produced. |
-| Unmaintained| 0 - 3 months | All bugfixes are appropriate. No Maintainers and No Releases produced. |
-| End Of Life (EOL) | N/A | Version no longer accepting changes. |
+## 版本维护状态
-## Maintenance status
+MindSpore 采用版本生命周期管理策略，详情如下：
-| **Version**| **Status** | **Initial Release Date**| **Next Phase** | **EOL Date**|
-|------------|--------------|--------------------------|----------------------------------------|-------------|
-| **r2.6** | Maintained | 2025-05-19 | Unmaintained
2026-05-19 estimated | 2026-05-19 |
-| **r2.5** | Maintained | 2025-02-08 | Unmaintained
2026-02-08 estimated | 2026-02-08 |
-| **r2.4** | Maintained | 2024-10-30 | Unmaintained
2025-10-30 estimated | 2025-10-30 |
-| **r2.3** | End Of Life | 2024-07-15 | | 2025-07-15 |
-| **r2.2** | End Of Life | 2023-10-18 | | 2024-10-18 |
-| **r2.1** | End Of Life | 2023-07-29 | | 2024-07-29 |
-| **r2.0** | End Of Life | 2023-06-15 | | 2024-06-15 |
-| **r1.10** | End Of Life | 2023-02-02 | | 2024-02-02 |
-| **r1.9** | End Of Life | 2022-10-26 | | 2023-10-26 |
-| **r1.8** | End Of Life | 2022-07-29 | | 2023-07-29 |
-| **r1.7** | End Of Life | 2022-04-29 | | 2023-04-29 |
-| **r1.6** | End Of Life | 2022-01-29 | | 2023-01-29 |
-| **r1.5** | End Of Life | 2021-10-15 | | 2022-10-15 |
-| **r1.4** | End Of Life | 2021-08-15 | | 2022-08-15 |
-| **r1.3** | End Of Life | 2021-07-15 | | 2022-07-15 |
-| **r1.2** | End Of Life | 2021-04-15 | | 2022-04-29 |
-| **r1.1** | End Of Life | 2020-12-31 | | 2021-09-30 |
-| **r1.0** | End Of Life | 2020-09-24 | | 2021-07-30 |
-| **r0.7** | End Of Life | 2020-08-31 | | 2021-02-28 |
-| **r0.6** | End Of Life | 2020-07-31 | | 2020-12-30 |
-| **r0.5** | End Of Life | 2020-06-30 | | 2021-06-30 |
-| **r0.3** | End Of Life | 2020-05-31 | | 2020-09-30 |
-| **r0.2** | End Of Life | 2020-04-30 | | 2020-08-31 |
-| **r0.1** | End Of Life | 2020-03-28 | | 2020-06-30 |
+| **版本** | **状态** | **初始发布时间** | **下一阶段** | **结束支持时间** |
+|----------|--------------|------------------|-------------------------------|----------------|
+| r2.6 | Maintained | 2025-05-19 | Unmaintained (2026-05-19) | 2026-05-19 |
+| r2.5 | Maintained | 2025-02-08 | Unmaintained (2026-02-08) | 2026-02-08 |
+| r2.4 | Maintained | 2024-10-30 | Unmaintained (2025-10-30) | 2025-10-30 |
+| r2.3 | End Of Life | 2024-07-15 | | 2025-07-15 |
+| r2.2 | End Of Life | 2023-10-18 | | 2024-10-18 |
+| r2.1 | End Of Life | 2023-07-29 | | 2024-07-29 |
+| r2.0 | End Of Life | 2023-06-15 | | 2024-06-15 |
+| r1.10 | End Of Life | 2023-02-02 | | 2024-02-02 |
-## Release Notes
+## 版本发布说明
-The release notes, see our [RELEASE](https://gitee.com/mindspore/mindspore/blob/master/RELEASE.md).
+最新版本的发布信息，请查看 [RELEASE.md](https://gitee.com/mindspore/mindspore/blob/master/RELEASE.md)。
-## License
+## 许可证
-[Apache License 2.0](https://gitee.com/mindspore/mindspore/blob/master/LICENSE)
+本项目使用 [Apache License 2.0](https://gitee.com/mindspore/mindspore/blob/master/LICENSE) 开源许可证。
\ No newline at end of file