app.py

import gradio as gr
from transformers import pipeline

sentiment_classifier = pipeline("text-classification", return_all_scores=True)

def classifier(text):
    pred = sentiment_classifier(text)
    return {p["label"]: p["score"] for p in pred[0]}

with gr.Blocks() as demo:
    with gr.Row():
        with gr.Column():
            input_text = gr.Textbox(label="Input Text")
            with gr.Row():
                classify = gr.Button("Done")
        with gr.Column():
            label = gr.Label(label="Predicted Sentiment")

    classify.click(classifier, input_text, label)
demo.launch()