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[NFC] add OPT serving (#1581)
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<a href="#推理-Energon-AI-样例展示">推理 (Energon-AI) 样例展示</a>
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<ul>
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<li><a href="#GPT-3-Inference">GPT-3</a></li>
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<li><a href="#OPT-Serving">1750亿参数OPT在线推理服务</a></li>
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</ul>
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</li>
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<li>
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@ -143,7 +144,7 @@ Colossal-AI 为您提供了一系列并行组件。我们的目标是让您的
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<img src="https://raw.githubusercontent.com/hpcaitech/public_assets/main/colossalai/img/OPT_update.png" width=800/>
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- [Open Pretrained Transformer (OPT)](https://github.com/facebookresearch/metaseq), 由Meta发布的1750亿语言模型,由于完全公开了预训练参数权重,因此促进了下游任务和应用部署的发展。
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- 加速45%,仅用几行代码以低成本微调OPT。[[样例]](https://github.com/hpcaitech/ColossalAI-Examples/tree/main/language/opt)
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- 加速45%,仅用几行代码以低成本微调OPT。[[样例]](https://github.com/hpcaitech/ColossalAI-Examples/tree/main/language/opt) [[在线推理]](https://service.colossalai.org/opt)
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请访问我们的 [文档](https://www.colossalai.org/) 和 [例程](https://github.com/hpcaitech/ColossalAI-Examples) 以了解详情。
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@ -176,13 +177,19 @@ Colossal-AI 为您提供了一系列并行组件。我们的目标是让您的
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## 推理 (Energon-AI) 样例展示
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### GPT-3
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<p id="GPT-3-Inference" align="center">
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<img src="https://raw.githubusercontent.com/hpcaitech/public_assets/main/colossalai/img/inference_GPT-3.jpg" width=800/>
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</p>
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- [Energon-AI](https://github.com/hpcaitech/EnergonAI) :用相同的硬件推理加速50%
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<p id="OPT-Serving" align="center">
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<img src="https://raw.githubusercontent.com/hpcaitech/public_assets/main/colossalai/img/OPT_serving.png" width=800/>
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</p>
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- [OPT推理服务](https://service.colossalai.org/opt): 无需注册,免费体验1750亿参数OPT在线推理服务
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<p align="right">(<a href="#top">back to top</a>)</p>
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## Colossal-AI 成功案例
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@ -196,6 +203,7 @@ Colossal-AI 为您提供了一系列并行组件。我们的目标是让您的
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- [xTrimoMultimer](https://github.com/biomap-research/xTrimoMultimer): 11倍加速蛋白质单体与复合物结构预测
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## 安装
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### 从官方安装
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10
README.md
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README.md
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<a href="#Inference-Energon-AI-Demo">Inference (Energon-AI) Demo</a>
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<ul>
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<li><a href="#GPT-3-Inference">GPT-3</a></li>
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<li><a href="#OPT-Serving">OPT-175B Online Serving for Text Generation</a></li>
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</ul>
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</li>
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<li>
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@ -148,7 +149,7 @@ distributed training and inference in a few lines.
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<img src="https://raw.githubusercontent.com/hpcaitech/public_assets/main/colossalai/img/OPT_update.png" width=800/>
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- [Open Pretrained Transformer (OPT)](https://github.com/facebookresearch/metaseq), a 175-Billion parameter AI language model released by Meta, which stimulates AI programmers to perform various downstream tasks and application deployments because public pretrained model weights.
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- 45% speedup fine-tuning OPT at low cost in lines. [[Example]](https://github.com/hpcaitech/ColossalAI-Examples/tree/main/language/opt)
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- 45% speedup fine-tuning OPT at low cost in lines. [[Example]](https://github.com/hpcaitech/ColossalAI-Examples/tree/main/language/opt) [[Online Serving]](https://service.colossalai.org/opt)
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Please visit our [documentation](https://www.colossalai.org/) and [examples](https://github.com/hpcaitech/ColossalAI-Examples) for more details.
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@ -181,13 +182,18 @@ Please visit our [documentation](https://www.colossalai.org/) and [examples](htt
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## Inference (Energon-AI) Demo
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### GPT-3
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<p id="GPT-3-Inference" align="center">
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<img src="https://raw.githubusercontent.com/hpcaitech/public_assets/main/colossalai/img/inference_GPT-3.jpg" width=800/>
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</p>
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- [Energon-AI](https://github.com/hpcaitech/EnergonAI): 50% inference acceleration on the same hardware
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<p id="OPT-Serving" align="center">
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<img src="https://raw.githubusercontent.com/hpcaitech/public_assets/main/colossalai/img/OPT_serving.png" width=800/>
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</p>
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- [OPT Serving](https://service.colossalai.org/opt): Try 175-billion-parameter OPT online services for free, without any registration whatsoever.
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<p align="right">(<a href="#top">back to top</a>)</p>
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## Colossal-AI in the Real World
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