Update app.py

app.py

@@ -1,14 +1,14 @@
 import gradio as gr
 from transformers import pipeline
 
-pipe = pipeline("text-classification", model="lewtun/xlm-roberta-base-finetuned-marc-500-samples")
+pipe = pipeline("text-classification", model="lewtun/xlm-roberta-base-finetuned-marc")
 
 def predict(text):
-  label2star = {"LABEL_0": "⭐", "LABEL_1": "⭐⭐", "LABEL_2": "⭐⭐⭐", "LABEL_3": "⭐⭐⭐⭐", "LABEL_4": "⭐⭐⭐⭐⭐"}
-  preds = pipe(text)[0]
-  return label2star[preds["label"]], round(preds["score"], 5)
+    label2emoji = {"terrible": "💩", "poor": "😾", "ok": "🐱", "good": "😺", "great": "😻"}
+    preds = pipe(text)[0]
+    return label2emoji[preds["label"]], round(preds["score"], 5)
   
-  gradio_ui = gr.Interface(
+gradio_ui = gr.Interface(
     fn=predict,
     title="Review analysis",
     description="Enter some review text about an Amazon product and check what the model predicts for it's star rating.",