trying custom_load_learner

app.py

@@ -177,12 +177,12 @@ categories = ('ABBOTTS BABBLER', 'ABBOTTS BOOBY', 'ABYSSINIAN GROUND HORNBILL',
 
 def load_learner_custom(fname):
     distrib_barrier()
-    res = torch.load(fname, map_location=torch.device('cpu'))
+    res = torch.load(fname)
     if hasattr(res, 'to_fp32'): res = res.to_fp32()
     return res
 
 
-learn = load_learner('best_model.pt')
+learn = load_learner_custom('best_model.pt')
 
 def classify_image(img):
     pred, idx, prbs = learn.predict(img)