From 68d0061937df406804238be2621c6abeefccf82b Mon Sep 17 00:00:00 2001
From: zhyncs <me@zhyncs.com>
Date: Mon, 30 Dec 2024 14:25:28 +0800
Subject: [PATCH] upd

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 README.md | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/README.md b/README.md
index 4fee2fd..1b8a59c 100644
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@@ -288,7 +288,7 @@ torchrun --nnodes 2 --nproc-per-node 8 generate.py --node-rank $RANK --master-ad
 
 ### 6.2 Inference with SGLang (recommended)
 
-[SGLang](https://github.com/sgl-project/sglang) currently supports MLA optimizations, FP8 (W8A8), FP8 KV Cache, and Torch Compile, delivering state-of-the-art latency and throughput performance among open-source frameworks.
+[SGLang](https://github.com/sgl-project/sglang) currently supports [MLA optimizations](https://lmsys.org/blog/2024-09-04-sglang-v0-3/#deepseek-multi-head-latent-attention-mla-throughput-optimizations), [DP Attention](https://lmsys.org/blog/2024-12-04-sglang-v0-4/#data-parallelism-attention-for-deepseek-models), FP8 (W8A8), FP8 KV Cache, and Torch Compile, delivering state-of-the-art latency and throughput performance among open-source frameworks.
 
 Notably, [SGLang v0.4.1](https://github.com/sgl-project/sglang/releases/tag/v0.4.1) fully supports running DeepSeek-V3 on both **NVIDIA and AMD GPUs**, making it a highly versatile and robust solution.