Add examples

app.py

@@ -7,7 +7,7 @@ from super_gradients.training import models
 import cv2
 import numpy as np
 
-device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
+device = torch.device("cpu")
 
 # Load the YOLO-NAS model
 yolo_nas_l = models.get("yolo_nas_l", pretrained_weights="coco")
@@ -95,7 +95,7 @@ model = load_model(model_path)
 # Gradio UI
 title = "Vehicle Collision Classification"
 description = "Upload an image to determine if it depicts a vehicle accident. Powered by EfficientNet."
-examples = [["roi_none.png"], ["test2.jpeg"]]  # Replace with your example image path
+examples = [["roi_none.png"], ["test2.jpeg"]]  
 
 gr.Interface(fn=lambda img: predict_image(img, model), 
              inputs=gr.inputs.Image(type="pil"),