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Ds ulysses news #4202

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Ds ulysses news #4202

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2 changes: 1 addition & 1 deletion README.md
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## Latest News
<b> <span style="color:orange" > DeepSpeed empowers ChatGPT-like model training with a single click, offering 15x speedup over SOTA RLHF systems with unprecedented cost reduction at all scales; [learn how](https://github.com/microsoft/DeepSpeed/tree/master/blogs/deepspeed-chat)</span>.</b>

* [2023/08] [DeepSpeed Ulysses: System Optimizations for Enabling Training of Extreme Long Sequence Transformer Models](https://github.com/microsoft/DeepSpeed/tree/master/blogs/deepspeed-ulysses)
* [2023/06] [ZeRO++: A leap in speed for LLM and chat model training with 4X less communication](https://www.microsoft.com/en-us/research/blog/deepspeed-zero-a-leap-in-speed-for-llm-and-chat-model-training-with-4x-less-communication/)[[English](https://www.microsoft.com/en-us/research/blog/deepspeed-zero-a-leap-in-speed-for-llm-and-chat-model-training-with-4x-less-communication/)] [[中文](https://github.com/microsoft/DeepSpeed/blob/master/blogs/zeropp/chinese/README.md)] [[日本語](https://github.com/microsoft/DeepSpeed/blob/master/blogs/zeropp/japanese/README.md)]
* [2023/04] 🚀 [DeepSpeed Chat: Easy, Fast and Affordable RLHF Training of ChatGPT-like Models at All Scales](https://github.com/microsoft/DeepSpeed/tree/master/blogs/deepspeed-chat) [[English](https://github.com/microsoft/DeepSpeed/tree/master/blogs/deepspeed-chat/README.md)] [[中文](https://github.com/microsoft/DeepSpeed/tree/master/blogs/deepspeed-chat/chinese/README.md)] [[日本語](https://github.com/microsoft/DeepSpeed/tree/master/blogs/deepspeed-chat/japanese/README.md)]🚀
* [2023/03] [Scaling Large-Scale Generative Mixture-of-Expert Multimodal Model With VL-MoE](https://www.deepspeed.ai/2023/03/30/multi-modal.html)
* [2023/02] [Automatic Tensor Parallelism: Enables tensor parallelism by default without an injection policy](https://www.deepspeed.ai/tutorials/automatic-tensor-parallelism/)
* [2022/12] [DeepSpeed Data Efficiency: A composable library that makes better use of data, increases training efficiency, and improves model quality](https://www.deepspeed.ai/2022/12/11/data-efficiency.html)

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2 changes: 1 addition & 1 deletion docs/index.md
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<b> <span style="color:orange" > DeepSpeed empowers ChatGPT-like model training with a single click, offering 15x speedup over SOTA RLHF systems with unprecedented cost reduction at all scales; [learn how](https://github.com/microsoft/DeepSpeed/tree/master/blogs/deepspeed-chat)</span>.</b>

* [2023/08] [DeepSpeed Ulysses: System Optimizations for Enabling Training of Extreme Long Sequence Transformer Models](https://github.com/microsoft/DeepSpeed/tree/master/blogs/deepspeed-ulysses)
* [2023/06] [ZeRO++: A leap in speed for LLM and chat model training with 4X less communication](https://www.microsoft.com/en-us/research/blog/deepspeed-zero-a-leap-in-speed-for-llm-and-chat-model-training-with-4x-less-communication/)[[English](https://www.microsoft.com/en-us/research/blog/deepspeed-zero-a-leap-in-speed-for-llm-and-chat-model-training-with-4x-less-communication/)] [[中文](https://github.com/microsoft/DeepSpeed/blob/master/blogs/zeropp/chinese/README.md)] [[日本語](https://github.com/microsoft/DeepSpeed/blob/master/blogs/zeropp/japanese/README.md)]
* [2023/04] 🚀 [DeepSpeed Chat: Easy, Fast and Affordable RLHF Training of ChatGPT-like Models at All Scales](https://github.com/microsoft/DeepSpeed/tree/master/blogs/deepspeed-chat) [[English](https://github.com/microsoft/DeepSpeed/tree/master/blogs/deepspeed-chat/README.md)] [[中文](https://github.com/microsoft/DeepSpeed/tree/master/blogs/deepspeed-chat/chinese/README.md)] [[日本語](https://github.com/microsoft/DeepSpeed/tree/master/blogs/deepspeed-chat/japanese/README.md)]🚀
* [2023/03] [Scaling Large-Scale Generative Mixture-of-Expert Multimodal Model With VL-MoE](https://www.deepspeed.ai/2023/03/30/multi-modal.html)
* [2023/02] [Automatic Tensor Parallelism: Enables tensor parallelism by default without an injection policy](https://www.deepspeed.ai/tutorials/automatic-tensor-parallelism/)
* [2022/12] [DeepSpeed Data Efficiency: A composable library that makes better use of data, increases training efficiency, and improves model quality](https://www.deepspeed.ai/2022/12/11/data-efficiency.html)


# Extreme Speed and Scale for DL Training and Inference
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