making it prettier

app.py

@@ -56,7 +56,7 @@ def predict(text, model_id, tokenizer_id):
 
     probs = torch.nn.functional.softmax(logits, dim=1).cpu().numpy().flatten()
     label_pred = model.config.id2label[probs.argmax()]
-    probability_pred = f"{100*probs.max()}%"
+    probability_pred = f"{round(100*probs.max(), 2)}%"
     return label_pred, probability_pred
 
 
@@ -83,8 +83,7 @@ with gr.Blocks() as demo:
             predict_button = gr.Button("Submit")
 
         with gr.Column():
-            result_table = gr.Dataframe(headers=["Sentence", "Prediction", "Probability"],
-                                        label="Sentence-level Predictions")
+            result_table = gr.Dataframe(headers=["Sentence", "Prediction", "Confidence"])
             model_info = gr.Markdown()
 
     predict_button.click(