Update app.py

app.py

@@ -177,7 +177,7 @@ multilabel_model = SkinViT(num_classes=len(multilabel_class_names))
 multiclass_model = DermNetViT(num_classes=len(multiclass_class_names))
 
 device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
-multilabel_model.load_state_dict(torch.load(multilabel_model_path, map_location=device))
+multilabel_model.load_state_dict(torch.load(multilabel_model_path, map_location="cpu"))
 multiclass_model.load_state_dict(torch.load(multiclass_model_path, map_location=device))
 multilabel_model.to(device)
 multiclass_model.to(device)
@@ -197,7 +197,7 @@ def run_inference(image):
         transforms.ToTensor(),
         transforms.Normalize([0.5], [0.5])
     ])
-    input_tensor = transform(image).unsqueeze(0).to(device)
+    input_tensor = transform(image).unsqueeze(0)
     with torch.no_grad():
         probs_multi = torch.sigmoid(multilabel_model(input_tensor)).squeeze().numpy()
         predicted_multi = [multilabel_class_names[i] for i, p in enumerate(probs_multi) if p > 0.5]