Update README.md

README.md

@@ -39,7 +39,9 @@ We introduce **GroveMoE**, a new sparse architecture using **adjugate experts**
 
 We bold the top1 scores separately for all models. More details are reported in our [technical report](https://arxiv.org/abs/2508.07785).
 
-## Usage
+## Run GroveMoE
+
+### 🤗 Transformers Quick Start
 Below, there are some code snippets on how to get quickly started with running the model. First, install the Transformers library. 
 
 ```sh
@@ -79,6 +81,52 @@ content = tokenizer.decode(output_ids, skip_special_tokens=True)
 print("content:", content)
 ```
 
+### 🚀 SGLang Quick Start
+For SGLang, you can follow the steps below to deploy:
+
+1️⃣ Install Dependencies
+
+First, clone the repository:
+```shell
+git clone https://github.com/inclusionAI/GroveMoE.git
+```
+Then, install Transformers:
+```shell
+cd src/transformers-4.51.3
+pip install .
+```
+Next, install SGLang:
+```shell
+cd src/sglang-0.4.6.post5
+pip install .
+
+```
+
+2️⃣ Launch the Server
+
+Run the following command to start SGLang:
+```shell
+python -m sglang.launch_server \
+  --model-path inclusionAI/GroveMoE-Inst \
+  --port 30000 \
+  --context-length 32768
+```
+
+3️⃣ Access the API
+
+Once started, the OpenAI-compatible API will be available at `http://localhost:30000/v1`.
+
+Test it with curl:
+```shell
+curl http://localhost:30000/v1/chat/completions \
+  -H "Content-Type: application/json" \
+  -d '{
+    "model": "inclusionAI/GroveMoE-Inst",
+    "messages": [{"role": "user", "content": "Hello, SGLang!"}]
+  }'
+
+```
+
 ## Citation
 ```bibtex
 @article{GroveMoE,