Added torch no_grad

app.py

@@ -15,12 +15,14 @@ for model_name, filename in model_options.items():
     print(f"Loading {model_name} ...")
     checkpoint_path = hf_hub_download(repo_id=repo_id, filename=filename, token=hf_token)
     models[model_name] = SmolLM.load_from_checkpoint(checkpoint_path)
+    models[model_name].eval()
 
 
 def classify_sentence(sentence, model_choice):
     model = models[model_choice]
-    inputs = model.tokenizer(sentence, return_tensors="pt", padding=True, truncation=True)
-    logits = model(inputs)
+    inputs = model.tokenizer(sentence, return_tensors="pt", padding=True, truncation=True, use_fast=True)
+    with torch.no_grad():
+        logits = model(inputs)
     confidence = torch.sigmoid(logits).item() * 100
     confidence_to_display = confidence if confidence > 50.0 else 100 - confidence
     label = "Complete" if confidence > 50.0 else "Incomplete"