carry model within decorator

app.py

@@ -7,7 +7,6 @@ from transformers import AutoImageProcessor, AutoModel
 import torch.nn.functional as F
 import spaces
 
-device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
 
 DINO_MODELS = {
     "DINOv3 Base ViT": "facebook/dinov3-vitb16-pretrain-lvd1689m", 
@@ -22,13 +21,15 @@ def load_model(model_name):
 
     processor = AutoImageProcessor.from_pretrained(model_path)
     model = AutoModel.from_pretrained(model_path)
-    model = model.to(device)
     return f"✅ Model '{model_name}' loaded successfully!"
 
 load_model("DINOv3 Base ViT")
 
 @spaces.GPU()
 def extract_features(image):
+    device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
+
+    model = model.to(device)
     original_size = image.size
     inputs = processor(images=image, return_tensors="pt")
     inputs = {k: v.to(device) for k, v in inputs.items()}