Update README.md

README.md

@@ -191,30 +191,34 @@ print(decoded_output)
 
 ### Serving
 
-You can utilize one of the following LLM inference frameworks to create an OpenAI compatible server: 
+The minimum hardware requirements for deploying Intern-S1 series models are:
+
+|                                  Model                                  | A100(GPUs) | H800(GPUs) | H100(GPUs) | H200(GPUs) |
+| :---------------------------------------------------------------------: | :--------: | :--------: | :--------: | :--------: |
+|     [internlm/Intern-S1](https://huggingface.co/internlm/Intern-S1)     |     8      |     8      |     8      |     4      |
+| [internlm/Intern-S1-FP8](https://huggingface.co/internlm/Intern-S1-FP8) |     -      |     4      |     4      |     2      |
+
+You can utilize one of the following LLM inference frameworks to create an OpenAI compatible server:
 
 #### [lmdeploy(>=0.9.2)](https://github.com/InternLM/lmdeploy)
 
-```
+```bash
 lmdeploy serve api_server internlm/Intern-S1 --reasoning-parser intern-s1 --tool-call-parser intern-s1 --tp 8
 ```
 
 #### [vllm](https://github.com/vllm-project/vllm)
 
-Coming soon.
+```bash
+vllm serve internlm/Intern-S1 --tensor-parallel-size 8 --trust-remote-code
+```
 
 #### [sglang](https://github.com/sgl-project/sglang)
 
-Supporting Intern-S1 with SGLang is still in progress. Please refer to this [PR](https://github.com/sgl-project/sglang/pull/8350).
-
 ```bash
-CUDA_VISIBLE_DEVICES=0,1,2,3,4,5,6,7 \
-    python3 -m sglang.launch_server \
+python3 -m sglang.launch_server \
     --model-path internlm/Intern-S1 \
     --trust-remote-code \
-    --mem-fraction-static 0.85 \
     --tp 8 \
-    --enable-multimodal \
     --grammar-backend none
 ```
 
@@ -225,7 +229,7 @@ CUDA_VISIBLE_DEVICES=0,1,2,3,4,5,6,7 \
 curl -fsSL https://ollama.com/install.sh | sh
 # fetch model
 ollama pull internlm/interns1
-# run model 
+# run model
 ollama run internlm/interns1
 # then use openai client to call on http://localhost:11434/v1
 ```