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[doc] update opt and tutorial links (#2509)
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@@ -149,7 +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) [[Online Serving]](https://service.colossalai.org/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://github.com/hpcaitech/ColossalAI-Documentation/blob/main/i18n/en/docusaurus-plugin-content-docs/current/advanced_tutorials/opt_service.md)
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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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@@ -202,7 +202,7 @@ Please visit our [documentation](https://www.colossalai.org/) and [examples](htt
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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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- [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.
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<p id="BLOOM-Inference" align="center">
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<img src="https://raw.githubusercontent.com/hpcaitech/public_assets/main/colossalai/img/BLOOM%20Inference.PNG" width=800/>
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@@ -369,4 +369,6 @@ We leverage the power of [GitHub Actions](https://github.com/features/actions) t
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}
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```
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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.
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<p align="right">(<a href="#top">back to top</a>)</p>
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