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feature: update REAEME, add online read link url

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@ -35,18 +35,20 @@
### 全书章节
+ [第一章：理解大语言模型](./cn-Book/1.理解大语言模型.md)
+ [第二章：处理文本数据](./cn-Book/2.处理文本数据.md)
+ [第三章：实现注意力机制](./cn-Book/3.实现注意力机制.md)
+ [第四章：从零开始实现一个用于文本生成的 GPT 模型](./cn-Book/4.从零开始实现一个用于文本生成的%20GPT%20模型.md)
+ [第五章：在无标记数据集上进行预训练](./cn-Book/5.在无标记数据集上进行预训练.md)
+ [第六章：用于分类任务的微调](./cn-Book/6.用于分类任务的微调.md)
+ [第七章：指令遵循微调](./cn-Book/7.指令遵循微调.md)
+ [附录A：PyTorch简介](./cn-Book/附录A.PyTorch简介.md)
+ [附录B：参考文献和扩展阅读](./cn-Book/附录B.参考文献和扩展阅读.md)
+ [附录C：习题解答](./cn-Book/附录C.习题解答.md)
+ [附录D：给训练循环添加高级技巧](./cn-Book/附录D.给训练循环添加高级技巧.md)
+ [附录E：使用 LoRA 的参数高效微调](./cn-Book/附录E.使用LoRA的参数高效微调.md)
**在线阅读**：[Build a Large Language Model (From Scratch) 中文版](https://skindhu.github.io/Build-A-Large-Language-Model-CN/)
+ [第一章：理解大语言模型](https://skindhu.github.io/Build-A-Large-Language-Model-CN/#/./cn-Book/1.理解大语言模型.md)
+ [第二章：处理文本数据](https://skindhu.github.io/Build-A-Large-Language-Model-CN/#/./cn-Book/2.处理文本数据.md)
+ [第三章：实现注意力机制](https://skindhu.github.io/Build-A-Large-Language-Model-CN/#/./cn-Book/3.实现注意力机制.md)
+ [第四章：从零开始实现一个用于文本生成的 GPT 模型](https://skindhu.github.io/Build-A-Large-Language-Model-CN/#/./cn-Book/4.从零开始实现一个用于文本生成的%20GPT%20模型.md)
+ [第五章：在无标记数据集上进行预训练](https://skindhu.github.io/Build-A-Large-Language-Model-CN/#/./cn-Book/5.在无标记数据集上进行预训练.md)
+ [第六章：用于分类任务的微调](https://skindhu.github.io/Build-A-Large-Language-Model-CN/#/./cn-Book/6.用于分类任务的微调.md)
+ [第七章：指令遵循微调](https://skindhu.github.io/Build-A-Large-Language-Model-CN/#/./cn-Book/7.指令遵循微调.md)
+ [附录A：PyTorch简介](https://skindhu.github.io/Build-A-Large-Language-Model-CN/#/./cn-Book/附录A.PyTorch简介.md)
+ [附录B：参考文献和扩展阅读](https://skindhu.github.io/Build-A-Large-Language-Model-CN/#/./cn-Book/附录B.参考文献和扩展阅读.md)
+ [附录C：习题解答](https://skindhu.github.io/Build-A-Large-Language-Model-CN/#/./cn-Book/附录C.习题解答.md)
+ [附录D：给训练循环添加高级技巧](https://skindhu.github.io/Build-A-Large-Language-Model-CN/#/./cn-Book/附录D.给训练循环添加高级技巧.md)
+ [附录E：使用 LoRA 的参数高效微调](https://skindhu.github.io/Build-A-Large-Language-Model-CN/#/./cn-Book/附录E.使用LoRA的参数高效微调.md)
## 个人思考