topk works a lot better when you actually use it

app.py

@@ -139,7 +139,7 @@ def run_classifier(image, threshold):
     with torch.no_grad():
         logits = model(tensor)
         probabilities = torch.nn.functional.sigmoid(logits[0])
-        indices = torch.where(probabilities, 250).indices
+        indices = torch.topk(probabilities, 250).indices
         values = probabilities[indices]
 
     tag_score = dict()