Update app.py

app.py

@@ -10,6 +10,7 @@ model = AutoModelForSequenceClassification.from_pretrained(model_name)
 # Function to compute relevance score
 def get_relevance_score(query, paragraph):
     inputs = tokenizer(query, paragraph, return_tensors="pt", truncation=True, padding=True)
+    model.eval()
     with torch.no_grad():
         scores = model(**inputs).logits.squeeze().item()
     return round(scores, 4)