update the readme doc (#639)

README.md

-<p align="center"><img width="40%" src="logo-Tengine.png" /></p>
+<div align="center">
+  <img width="40%" src="logo-Tengine.png">
+  <h3> <a href="https://tengine-docs.readthedocs.io/en/latest/"> Documentation </a> | <a href="https://tengine-docs.readthedocs.io/zh_CN/latest/"> 中文文档 </a>  </h3>
+</div>
 
-# Tengine Lite
+简体中文 | [English](./README_EN.md)
+
+# Tengine
 
 [![GitHub license](http://OAID.github.io/pics/apache_2.0.svg)](./LICENSE)
 [![Build Status](https://img.shields.io/github/workflow/status/OAID/Tengine/Tengine-Lite-Actions/tengine-lite)](https://github.com/OAID/Tengine/actions?query=workflow%3ATengine-Lite-Actions)
@@ -10,11 +15,6 @@
 [![Language grade: C/C++](https://img.shields.io/lgtm/grade/cpp/g/OAID/Tengine.svg?logo=lgtm&logoWidth=18)](https://lgtm.com/projects/g/OAID/Tengine/context:cpp)
 
 
-
-[**English Version**](README_EN.md)
-
-
-
 ## 简介
 
 **Tengine** 由 **[OPEN AI LAB](http://www.openailab.com)** 主导开发，该项目实现了深度学习神经网络模型在嵌入式设备上的**快速**、**高效**部署需求。为实现在众多 **AIoT** 应用中的跨平台部署，本项目使用 **C 语言**进行核心模块开发，针对嵌入式设备资源有限的特点进行了深度框架裁剪。同时采用了完全分离的前后端设计，有利于 CPU、GPU、NPU 等异构计算单元的快速移植和部署，降低评估、迁移成本。
@@ -33,10 +33,6 @@ Tengine 核心代码由 4 个模块组成：
 
 ## 快速上手
 
-### 在线文档
-
-- [Tengine 用户使用手册](https://tengine-docs.readthedocs.io/zh_CN/latest/)
-
 ### 编译
 
 - [快速编译](doc/compile.md) 基于 cmake 实现简单的跨平台编译。

README_EN.md

-<p align="center"><img width="40%" src="logo-Tengine.png" /></p>
+<div align="center">
+  <img width="40%" src="logo-Tengine.png">
+  <h3> <a href="https://tengine-docs.readthedocs.io/en/latest/"> Documentation </a> | <a href="https://tengine-docs.readthedocs.io/zh_CN/latest/"> 中文文档 </a>  </h3>
+</div>
 
-# Tengine Lite
+English | [简体中文](./README.md)
+
+# Tengine
 
 [![GitHub license](http://OAID.github.io/pics/apache_2.0.svg)](./LICENSE)
 [![Build Status](https://img.shields.io/github/workflow/status/OAID/Tengine/Tengine-Lite-Actions/tengine-lite)](https://github.com/OAID/Tengine/actions?query=workflow%3ATengine-Lite-Actions)
@@ -10,11 +15,6 @@
 [![Language grade: C/C++](https://img.shields.io/lgtm/grade/cpp/g/OAID/Tengine.svg?logo=lgtm&logoWidth=18)](https://lgtm.com/projects/g/OAID/Tengine/context:cpp)
 
 
-
-[**中文版本**](README.md)
-
-
-
 ## Introduction
 
 **Tengine** is developed by **[OPEN AI LAB](http://www.openailab.com)**. This project meet the demand of **fast** and **efficient** deployment of deep learning neural network models on embedded devices. In order to achieve cross-platform deployment in many **AIoT** applications, this project is based on the original Tengine project using **C language** for reconstruction, and deep frame tailoring for the characteristics of limited embedded device resources. Also, it adopts a completely separated front-end/back-end design, which makes it possible to be transplanted and deployed onto CPU, GPU, NPU and other heterogeneous computing units rapidly, conveniently. At the same time, it is compatible with the original API and model format `tmfile` of **Tengine**, which reduces the cost of evaluation and migration.
@@ -36,10 +36,6 @@ The core code of Tengine Lite consists of 4 modules:
 
 ## How to use
 
-### Documentation
-
-- [Tengine User Manual](https://tengine-docs.readthedocs.io/en/latest/)
-
 ### Compile
 
 - [Quick Compilation](doc/compile.md) Simple cross-platform compilation based on cmake.