modified app.py gradio cuda

app.py

@@ -26,7 +26,7 @@ device = torch.device("cuda:0" if torch.cuda.is_available() else "cpu")
 
 
 # Load CWM 3-frame model (automatically download pre-trained checkpoint)
-model = model_factory.load_model('vitb_8x8patch_3frames').to(device)
+model = model_factory.load_model('vitb_8x8patch_3frames')#.to(device)
 
 model.requires_grad_(False)
 model.eval()
@@ -91,7 +91,7 @@ import os
 # print("Preloaded images:", preloaded_images)
 @spaces.GPU
 def get_c(x, points):
-    x = utils.imagenet_normalize(x).to(device)
+    x = utils.imagenet_normalize(x)#.to(device)
     with torch.no_grad():
         counterfactual = model.get_counterfactual(x, points)
     return counterfactual