From 408e6e188a6a583370c66d3c0f85fc8a68b8a4c6 Mon Sep 17 00:00:00 2001
From: shihaobai <42648726+shihaobai@users.noreply.github.com>
Date: Mon, 3 Mar 2025 20:16:37 +0800
Subject: [PATCH] Update README.md

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

diff --git a/README.md b/README.md
index 920ca51..9e5f08b 100644
--- a/README.md
+++ b/README.md
@@ -331,7 +331,7 @@ For comprehensive step-by-step instructions on running DeepSeek-V3 with LMDeploy
 
 ### 6.6 Inference with LightLLM (recommended)
 
-[LightLLM](https://github.com/ModelTC/lightllm/tree/main) LightLLM v1.0.1 supports single-machine and multi-machine tensor parallel deployment for DeepSeek-R1 (FP8/BF16) and provides mixed-precision deployment, with more quantization modes continuously integrated. For more details, please refer to [LightLLM instructions](https://lightllm-en.readthedocs.io/en/latest/getting_started/quickstart.html). Additionally, LightLLM offers PD-disaggregation deployment for DeepSeek-V2, and the implementation of PD-disaggregation for DeepSeek-V3 is in development.
+[LightLLM](https://github.com/ModelTC/lightllm/tree/main) v1.0.1 supports single-machine and multi-machine tensor parallel deployment for DeepSeek-R1 (FP8/BF16) and provides mixed-precision deployment, with more quantization modes continuously integrated. For more details, please refer to [LightLLM instructions](https://lightllm-en.readthedocs.io/en/latest/getting_started/quickstart.html). Additionally, LightLLM offers PD-disaggregation deployment for DeepSeek-V2, and the implementation of PD-disaggregation for DeepSeek-V3 is in development.
 
 ### 6.7 Recommended Inference Functionality with AMD GPUs