Update README.md to include SGLang instruction

README.md

@@ -215,6 +215,99 @@ print(response.json()["choices"][0]["message"]["content"])
 ```
 </details>
 
+#### SGLang (recommended)
+
+<details>
+<summary>Expand</summary>
+
+We recommend using this model with [SGLang](https://github.com/sgl-project/sglang)
+to implement production-ready inference pipelines (OpenAI-compatible API server).
+
+**_Installation_**
+
+Install SGLang from source (track latest `main` locally):
+
+```
+git clone https://github.com/sgl-project/sglang.git
+cd sglang
+uv pip install -e python
+uv pip install transformers==5.0.0rc # required
+```
+
+**_Launch server_**
+
+We recommend that you use Devstral in a server/client setting.
+
+1. Spin up a server:
+
+```
+python -m sglang.launch_server --model-path mistralai/Devstral-2-123B-Instruct-2512 --host 0.0.0.0 --port 30000 --tp 8 --tool-call-parser mistral
+```
+
+
+2. To ping the client you can use a simple Python snippet.
+
+```py
+import requests
+import json
+from huggingface_hub import hf_hub_download
+
+
+url = "http://<your-server-url>:30000/v1/chat/completions"
+headers = {"Content-Type": "application/json", "Authorization": "Bearer token"}
+
+model = "mistralai/Devstral-2-123B-Instruct-2512"
+
+def load_system_prompt(repo_id: str, filename: str) -> str:
+    file_path = hf_hub_download(repo_id=repo_id, filename=filename)
+    with open(file_path, "r") as file:
+        system_prompt = file.read()
+    return system_prompt
+
+SYSTEM_PROMPT = load_system_prompt(model, "CHAT_SYSTEM_PROMPT.txt")
+
+messages = [
+    {"role": "system", "content": SYSTEM_PROMPT},
+    {
+        "role": "user",
+        "content": [
+            {
+                "type": "text",
+                "text": "<your-command>",
+            },
+        ],
+    },
+]
+
+data = {"model": model, "messages": messages, "temperature": 0.15}
+
+# Devstral 2 supports tool calling. If you want to use tools, follow this:
+# tools = [  # Define tools (OpenAI-compatible)
+#     {
+#         "type": "function",
+#         "function": {
+#             "name": "git_clone",
+#             "description": "Clone a git repository",
+#             "parameters": {
+#                 "type": "object",
+#                 "properties": {
+#                     "url": {
+#                         "type": "string",
+#                         "description": "The url of the git repository",
+#                     },
+#                 },
+#                 "required": ["url"],
+#             },
+#         },
+#     }
+# ] 
+# data = {"model": model, "messages": messages, "temperature": 0.15, "tools": tools} # Pass tools to payload.
+
+response = requests.post(url, headers=headers, data=json.dumps(data))
+print(response.json()["choices"][0]["message"]["content"])
+```
+</details>
+
 #### Transformers
 
 <details>