app.py

import gradio as gr
import torch
from transformers import pipeline

device = 0 if torch.cuda.is_available() else -1

sentiment_pipeline = pipeline("text-classification", 
                              model="winain7788/bert-finetuned-sem_eval-english", 
                              device=device)

async def get_sentiment(text):
    return sentiment_pipeline([text])

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

demo.launch()