Update infinity section in readme

README.md

@@ -2904,7 +2904,7 @@ from infinity_emb import AsyncEmbeddingEngine, EngineArgs
 
 sentences = ["Embed this is sentence via Infinity.", "Paris is in France."]
 engine = AsyncEmbeddingEngine.from_args(
-    EngineArgs(model_name_or_path = "BAAI/bge-large-en-v1.5", device="cpu", engine="optimum" # or engine="torch"
+    EngineArgs(model_name_or_path = "BAAI/bge-base-en-v1.5", device="cpu", engine="optimum" # or engine="torch"
 ))
 
 async def main(): 
@@ -2913,6 +2913,13 @@ async def main():
 asyncio.run(main())
 ```
 
+for a docker based deployment with infinity using torch:
+```bash
+docker run --gpus all -v $PWD/data:/app/.cache -p "7997":"7997" \
+michaelf34/infinity:0.0.68 \
+v2 --model-id BAAI/bge-base-en-v1.5 --revision "main" --dtype float16 --batch-size 32 --engine torch --port 7997
+```
+
 ### Usage for Reranker
 
 Different from embedding model, reranker uses question and document as input and directly output similarity instead of embedding.