diff --git a/README.md b/README.md
index 84e3c9416..5f643fd5d 100644
--- a/README.md
+++ b/README.md
@@ -144,12 +144,12 @@ import torch
 from yolort.runtime import PredictorTRT
 
 # Load the exported TensorRT engine
-engine_path = 'yolov5n6.engine'
-device = torch.device('cuda')
+engine_path = "yolov5n6.engine"
+device = torch.device("cuda")
 y_runtime = PredictorTRT(engine_path, device=device)
 
 # Perform inference on an image file
-predictions = y_runtime.predict('bus.jpg')
+predictions = y_runtime.predict("bus.jpg")
 ```
 
 On the `TensorRT` front you can use the [C++ example](deployment/tensorrt), and we also provide a [tutorial](https://zhiqwang.com/yolov5-rt-stack/notebooks/onnx-graphsurgeon-inference-tensorrt.html) for using the `TensorRT`.