From 46a392658e3a968fe5284a58af21641683b32f6e Mon Sep 17 00:00:00 2001 From: Lianmin Zheng Date: Wed, 18 Mar 2026 12:43:42 -0700 Subject: [PATCH] Refine RL & Post-Training description in README (#20877) Co-authored-by: Claude Opus 4.6 (1M context) --- README.md | 2 +- docs/index.rst | 2 +- 2 files changed, 2 insertions(+), 2 deletions(-) diff --git a/README.md b/README.md index e91051734..77f647551 100644 --- a/README.md +++ b/README.md @@ -63,7 +63,7 @@ Its core features include: - **Broad Model Support**: Supports a wide range of language models (Llama, Qwen, DeepSeek, Kimi, GLM, GPT, Gemma, Mistral, etc.), embedding models (e5-mistral, gte, mcdse), reward models (Skywork), and diffusion models (WAN, Qwen-Image), with easy extensibility for adding new models. Compatible with most Hugging Face models and OpenAI APIs. - **Extensive Hardware Support**: Runs on NVIDIA GPUs (GB200/B300/H100/A100/Spark), AMD GPUs (MI355/MI300), Intel Xeon CPUs, Google TPUs, Ascend NPUs, and more. - **Active Community**: SGLang is open-source and supported by a vibrant community with widespread industry adoption, powering over 400,000 GPUs worldwide. -- **RL & Post-Training Backbone**: SGLang is a proven rollout backend across the world, with native RL integrations and adoption by well-known post-training frameworks such as [**AReaL**](https://github.com/inclusionAI/AReaL), [**Miles**](https://github.com/radixark/miles), [**slime**](https://github.com/THUDM/slime), [**Tunix**](https://github.com/google/tunix), [**verl**](https://github.com/volcengine/verl) and more. +- **RL & Post-Training Backbone**: SGLang is a proven rollout backend used for training many frontier models, with native RL integrations and adoption by well-known post-training frameworks such as [**AReaL**](https://github.com/inclusionAI/AReaL), [**Miles**](https://github.com/radixark/miles), [**slime**](https://github.com/THUDM/slime), [**Tunix**](https://github.com/google/tunix), [**verl**](https://github.com/volcengine/verl) and more. ## Getting Started - [Install SGLang](https://docs.sglang.io/get_started/install.html) diff --git a/docs/index.rst b/docs/index.rst index def5f5959..60f52afc6 100644 --- a/docs/index.rst +++ b/docs/index.rst @@ -16,7 +16,7 @@ Its core features include: - **Broad Model Support**: Supports a wide range of language models (Llama, Qwen, DeepSeek, Kimi, GLM, GPT, Gemma, Mistral, etc.), embedding models (e5-mistral, gte, mcdse), reward models (Skywork), and diffusion models (WAN, Qwen-Image), with easy extensibility for adding new models. Compatible with most Hugging Face models and OpenAI APIs. - **Extensive Hardware Support**: Runs on NVIDIA GPUs (GB200/B300/H100/A100/Spark), AMD GPUs (MI355/MI300), Intel Xeon CPUs, Google TPUs, Ascend NPUs, and more. - **Active Community**: SGLang is open-source and supported by a vibrant community with widespread industry adoption, powering over 400,000 GPUs worldwide. -- **RL & Post-Training Backbone**: SGLang is a proven rollout backend across the world, with native RL integrations and adoption by well-known post-training frameworks such as AReaL, Miles, slime, Tunix, verl and more. +- **RL & Post-Training Backbone**: SGLang is a proven rollout backend used for training many frontier models, with native RL integrations and adoption by well-known post-training frameworks such as AReaL, Miles, slime, Tunix, verl and more. .. toctree:: :maxdepth: 1