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[doc] add ColossalChat (#3297) 

* [doc] add ColossalChat
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21
README.md
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@ -66,7 +66,7 @@
<li>
<a href="#Colossal-AI-in-the-Real-World">Colossal-AI for Real World Applications</a>
<ul>
<li><a href="#ChatGPT">ChatGPT: Low-cost ChatGPT Equivalent Implementation Process</a></li>
<li><a href="#ColossalChat">ColossalChat: An Open-Source Solution for Cloning ChatGPT With a Complete RLHF Pipeline</a></li>
<li><a href="#AIGC">AIGC: Acceleration of Stable Diffusion</a></li>
<li><a href="#Biomedicine">Biomedicine: Acceleration of AlphaFold Protein Structure</a></li>
</ul>
@ -214,22 +214,31 @@ Please visit our [documentation](https://www.colossalai.org/) and [examples](htt
<p align="right">(<a href="#top">back to top</a>)</p>
## Colossal-AI in the Real World
### ChatGPT
A low-cost [ChatGPT](https://openai.com/blog/chatgpt/) equivalent implementation process. [[code]](https://github.com/hpcaitech/ColossalAI/tree/main/applications/ChatGPT) [[blog]](https://www.hpc-ai.tech/blog/colossal-ai-chatgpt)
<p id="ChatGPT_scaling" align="center">
### ColossalChat
<div align="center">
<a href="https://chat.colossalai.org/">
<img src="https://raw.githubusercontent.com/hpcaitech/public_assets/main/colossalai/img/Chat-demo.png" width="700" />
</a>
</div>
[ColossalChat](https://github.com/hpcaitech/ColossalAI/tree/main/applications/Chat): An open-source solution for cloning [ChatGPT](https://openai.com/blog/chatgpt/) with a complete RLHF pipeline. [[code]](https://github.com/hpcaitech/ColossalAI/tree/main/applications/Chat) [[blog]](https://www.hpc-ai.tech/blog/colossal-ai-chatgpt) [[demo]](https://chat.colossalai.org)
<p id="ColossalChat_scaling" align="center">
<img src="https://raw.githubusercontent.com/hpcaitech/public_assets/main/applications/chatgpt/ChatGPT%20scaling.png" width=800/>
</p>
- Up to 7.73 times faster for single server training and 1.42 times faster for single-GPU inference
<p id="ChatGPT-1GPU" align="center">
<p id="ColossalChat-1GPU" align="center">
<img src="https://raw.githubusercontent.com/hpcaitech/public_assets/main/applications/chatgpt/ChatGPT-1GPU.jpg" width=450/>
</p>
- Up to 10.3x growth in model capacity on one GPU
- A mini demo training process requires only 1.62GB of GPU memory (any consumer-grade GPU)
<p id="inference" align="center">
<p id="ColossalChat-LoRA" align="center">
<img src="https://raw.githubusercontent.com/hpcaitech/public_assets/main/applications/chatgpt/LoRA%20data.jpg" width=600/>
</p>

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docs/README-zh-Hans.md
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@ -66,7 +66,7 @@
<li>
<a href="#Colossal-AI-in-the-Real-World">Colossal-AI 成功案例</a>
<ul>
<li><a href="#ChatGPT">ChatGPT: 低成本复现ChatGPT完整流程</a></li>
<li><a href="#ColossalChat">ColossalChat：完整RLHF流程0门槛克隆ChatGPT</a></li>
<li><a href="#AIGC">AIGC: 加速 Stable Diffusion</a></li>
<li><a href="#生物医药">生物医药: 加速AlphaFold蛋白质结构预测</a></li>
</ul>
@ -212,22 +212,30 @@ Colossal-AI 为您提供了一系列并行组件。我们的目标是让您的
<p align="right">(<a href="#top">返回顶端</a>)</p>
## Colossal-AI 成功案例
### ChatGPT
低成本复现[ChatGPT](https://openai.com/blog/chatgpt/)完整流程 [[代码]](https://github.com/hpcaitech/ColossalAI/tree/main/applications/ChatGPT) [[博客]](https://www.hpc-ai.tech/blog/colossal-ai-chatgpt)
<p id="ChatGPT_scaling" align="center">
### ColossalChat
<div align="center">
<a href="https://chat.colossalai.org/">
<img src="https://raw.githubusercontent.com/hpcaitech/public_assets/main/colossalai/img/Chat-demo.png" width="700" />
</a>
</div>
[ColossalChat](https://github.com/hpcaitech/ColossalAI/tree/main/applications/Chat): 完整RLHF流程0门槛克隆 [ChatGPT](https://openai.com/blog/chatgpt/) [[代码]](https://github.com/hpcaitech/ColossalAI/tree/main/applications/Chat) [[博客]](https://www.hpc-ai.tech/blog/colossal-ai-chatgpt) [[在线样例]](https://chat.colossalai.org)
<p id="ColossalChat_scaling" align="center">
<img src="https://raw.githubusercontent.com/hpcaitech/public_assets/main/applications/chatgpt/ChatGPT%20scaling.png" width=800/>
</p>
- 最高可提升单机训练速度7.73倍，单卡推理速度1.42倍
<p id="ChatGPT-1GPU" align="center">
<p id="ColossalChat-1GPU" align="center">
<img src="https://raw.githubusercontent.com/hpcaitech/public_assets/main/applications/chatgpt/ChatGPT-1GPU.jpg" width=450/>
</p>
- 单卡模型容量最多提升10.3倍
- 最小demo训练流程最低仅需1.62GB显存 (任意消费级GPU)
<p id="inference" align="center">
<p id="ColossalChat-LoRA" align="center">
<img src="https://raw.githubusercontent.com/hpcaitech/public_assets/main/applications/chatgpt/LoRA%20data.jpg" width=600/>
</p>