From a6a10616ec2dafca6640efd2d2e4029e2469512c Mon Sep 17 00:00:00 2001
From: binmakeswell
@@ -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。 +
(返回顶端)
diff --git a/README.md b/README.md index 396260e97..01e7b0ec5 100644 --- a/README.md +++ b/README.md @@ -149,7 +149,7 @@ distributed training and inference in a few lines. - [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. @@ -202,7 +202,7 @@ Please visit our [documentation](https://www.colossalai.org/) and [examples](htt -- [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.@@ -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. +