app.py

import gradio as gr
from transformers import pipeline

pipe = pipeline("text-classification", model="lewtun/xlm-roberta-base-finetuned-marc")

label2emoji = {"terrible": "💩", "poor": "😾", "ok": "🐱", "good": "😺", "great": "😻"}

def predict(text):
    preds = pipe(text)[0]
    return label2emoji[preds["label"]], round(preds["score"], 5)
    
gradio_ui = gr.Interface(
    fn=predict,
    title="Predicting review scores from customer reviews",
    description="Enter some review text about an Amazon product and check what the model predicts for it's star rating.",
    inputs=[
        gr.inputs.Textbox(lines=5, label="Paste some text here"),
    ],
    outputs=[
        gr.outputs.Textbox(label="Label"),
        gr.outputs.Textbox(label="Score"),
    ],
    examples=[
        ["I love these running shoes"], ["J'adore ces chaussures de course"], ["Ich liebe diese Laufschuhe"]
    ],
)

gradio_ui.launch(debug=True)