no grad

app.py

@@ -35,7 +35,8 @@ def predict (Sentence, Word, LLM, Norm, Layer):
 
     data = (Sentence, Word)
     emb = lm.extract_representation(data, layer=Layer)
-    pred = torch.nn.functional.relu(model(emb))
+    with torch.no_grad:
+        pred = torch.nn.functional.relu(model(emb))
     pred_sq = pred.squeeze(0)
     pred_round = torch.round(pred_sq, decimals=2)
     pred_list = pred_round.detach().numpy().tolist()