sentence

app.py

@@ -68,7 +68,7 @@ def predict(text, model_id, tokenizer_id):
 def get_most_probable_label(probs):
     label = id2label[probs.argmax()]
     probability = f"{round(100 * probs.max(), 2)}%"
-    return [sentence, label, probability]
+    return label, probability
 
 def predict_wrapper(text, language):
     model_id = build_huggingface_path(language)
@@ -80,7 +80,7 @@ def predict_wrapper(text, language):
     results = []
     for sentence in sentences:
         probs = predict(sentence, model_id, tokenizer_id)
-        results.append(get_most_probable_label(probs))
+        results.append(sentence, get_most_probable_label(probs))
 
     output_info = f'Prediction was made using the <a href="https://huggingface.co/{model_id}">{model_id}</a> model.'
     return results, output_info