Update app.py

app.py

@@ -28,8 +28,9 @@ cats = ["Computer Science", "Economics", "Electrical Engineering",
 
 def predict(outputs):
     top = 0
-    temp = 0.5
-    probs = nn.functional.softmax(outputs / temp, dim=1).tolist()[0]
+    temp = 30000
+    apr_probs = torch.nn.functional.softmax(torch.tensor([39253., 84., 220., 2263., 1214., 909., 66., 10661.]) / temp, dim=0)
+    probs = nn.functional.softmax(outputs * apr_probs, dim=1).tolist()[0]
     
     top_cats = []
     top_probs = []