Update app.py

app.py

@@ -4,7 +4,7 @@ from transformers import pipeline
 pipe = pipeline(model="delarosajav95/tw-roberta-base-sentiment-FT-v2")
 #function that Gradio will use to classify
 def classify_text(inputs):
-  result = pipe(inputs, return_all_scores=True)
+  result = pipe(inputs, top_k=None)
   output = []
   label_mapping = {"LABEL_0": "Negative", "LABEL_1": "Neutral", "LABEL_2": "Positive"}
   for i, predictions in enumerate(result):
@@ -30,4 +30,4 @@ iface = gr.Interface(
 )
 
 # Launch the interface
-iface.launch(share=True)
+iface.launch()