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[doc] update opt and tutorial links (#2509)

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binmakeswell 2 years ago committed by GitHub
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  1. 6
      README-zh-Hans.md
  2. 6
      README.md

6
README-zh-Hans.md

@ -145,7 +145,7 @@ Colossal-AI 为您提供了一系列并行组件。我们的目标是让您的
<img src="https://raw.githubusercontent.com/hpcaitech/public_assets/main/colossalai/img/OPT_update.png" width=800/> <img src="https://raw.githubusercontent.com/hpcaitech/public_assets/main/colossalai/img/OPT_update.png" width=800/>
- [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。 - [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。
- 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) - 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://github.com/hpcaitech/ColossalAI-Documentation/blob/main/i18n/zh-Hans/docusaurus-plugin-content-docs/current/advanced_tutorials/opt_service.md)
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。 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。
@ -199,7 +199,7 @@ Colossal-AI 为您提供了一系列并行组件。我们的目标是让您的
<img src="https://raw.githubusercontent.com/hpcaitech/public_assets/main/colossalai/img/OPT_serving.png" width=800/> <img src="https://raw.githubusercontent.com/hpcaitech/public_assets/main/colossalai/img/OPT_serving.png" width=800/>
</p> </p>
- [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 - [OPT推理服务](https://github.com/hpcaitech/ColossalAI-Documentation/blob/main/i18n/zh-Hans/docusaurus-plugin-content-docs/current/advanced_tutorials/opt_service.md): 无需注册,免费体验1750亿参数OPT在线推理服务
<p id="BLOOM-Inference" align="center"> <p id="BLOOM-Inference" align="center">
<img src="https://raw.githubusercontent.com/hpcaitech/public_assets/main/colossalai/img/BLOOM%20Inference.PNG" width=800/> <img src="https://raw.githubusercontent.com/hpcaitech/public_assets/main/colossalai/img/BLOOM%20Inference.PNG" width=800/>
@ -365,4 +365,6 @@ docker run -ti --gpus all --rm --ipc=host colossalai bash
} }
``` ```
Colossal-AI 已被 [SC](https://sc22.supercomputing.org/), [AAAI](https://aaai.org/Conferences/AAAI-23/), [PPoPP](https://ppopp23.sigplan.org/) 等顶级会议录取为官方教程。
<p align="right">(<a href="#top">返回顶端</a>)</p> <p align="right">(<a href="#top">返回顶端</a>)</p>

6
README.md

@ -149,7 +149,7 @@ distributed training and inference in a few lines.
<img src="https://raw.githubusercontent.com/hpcaitech/public_assets/main/colossalai/img/OPT_update.png" width=800/> <img src="https://raw.githubusercontent.com/hpcaitech/public_assets/main/colossalai/img/OPT_update.png" width=800/>
- [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. - [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.
- 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) - 45% speedup fine-tuning OPT at low cost in lines. [[Example]](https://github.com/hpcaitech/ColossalAI-Examples/tree/main/language/opt) [[Online Serving]](https://github.com/hpcaitech/ColossalAI-Documentation/blob/main/i18n/en/docusaurus-plugin-content-docs/current/advanced_tutorials/opt_service.md)
Please visit our [documentation](https://www.colossalai.org/) and [examples](https://github.com/hpcaitech/ColossalAI-Examples) for more details. Please visit our [documentation](https://www.colossalai.org/) and [examples](https://github.com/hpcaitech/ColossalAI-Examples) for more details.
@ -202,7 +202,7 @@ Please visit our [documentation](https://www.colossalai.org/) and [examples](htt
<img src="https://raw.githubusercontent.com/hpcaitech/public_assets/main/colossalai/img/OPT_serving.png" width=800/> <img src="https://raw.githubusercontent.com/hpcaitech/public_assets/main/colossalai/img/OPT_serving.png" width=800/>
</p> </p>
- [OPT Serving](https://service.colossalai.org/opt): Try 175-billion-parameter OPT online services for free, without any registration whatsoever. - [OPT Serving](https://github.com/hpcaitech/ColossalAI-Documentation/blob/main/i18n/en/docusaurus-plugin-content-docs/current/advanced_tutorials/opt_service.md): Try 175-billion-parameter OPT online services for free, without any registration whatsoever.
<p id="BLOOM-Inference" align="center"> <p id="BLOOM-Inference" align="center">
<img src="https://raw.githubusercontent.com/hpcaitech/public_assets/main/colossalai/img/BLOOM%20Inference.PNG" width=800/> <img src="https://raw.githubusercontent.com/hpcaitech/public_assets/main/colossalai/img/BLOOM%20Inference.PNG" width=800/>
@ -369,4 +369,6 @@ We leverage the power of [GitHub Actions](https://github.com/features/actions) t
} }
``` ```
Colossal-AI has been accepted as official tutorials by top conference [SC](https://sc22.supercomputing.org/), [AAAI](https://aaai.org/Conferences/AAAI-23/), [PPoPP](https://ppopp23.sigplan.org/), etc.
<p align="right">(<a href="#top">back to top</a>)</p> <p align="right">(<a href="#top">back to top</a>)</p>

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