app.py

import gradio as gr
from transformers import pipeline

sentiment_classifier = pipeline(
    model="lxyuan/distilbert-base-multilingual-cased-sentiments-student", 
    return_all_scores=True
)

def get_sentiment(input):
    s = sentiment_classifier (input)[0][0]['score']
    if s < 0.2:
        return 1
    elif s < 0.4:
        return 2
    elif s < 0.6:
        return 3
    elif s < 0.8:
        return 4
    return 5

gr.close_all()
demo = gr.Interface(fn=get_sentiment, inputs="text", outputs="text")
demo.launch()