Update app.py

app.py

@@ -6,14 +6,11 @@ device=torch.device("cuda" if torch.cuda.is_available() else "cpu")
 
 
 # Cargamos el learner
-#def load(map_location='cpu', pickle_module=pickle, **pickle_load_args):
-#    with open ('modelomemes.pkl',mode='rb') as file:
-#        learn=torch.load(cloudpickle.load(file), map_location="cpu")
+def load(map_location='cpu', pickle_module=pickle, **pickle_load_args):
+    with open ('modelomemes.pkl',mode='rb') as file:
+        learn=torch.load(cloudpickle.load(file), map_location="cpu")
     
-learn = Net()
-learn.load_state_dict(torch.load('./ElModeloMemes.pth', map_location=device))
-learn.to(device)
-
+load()
 
 # Definimos una función que se encarga de llevar a cabo las predicciones
 def predict(img):