sentment.py

# -*- coding: utf-8 -*-
"""Sentment.ipynb

Automatically generated by Colab.

Original file is located at
    https://colab.research.google.com/drive/1ivaq7Q88JAMMQT4pr7ms9q6ZxAR4niVn
"""

import gradio as gr
from transformers import pipeline

# Load the pre-trained model
classifier = pipeline('sentiment-analysis')

# Define the prediction function
def predict_sentiment(text):
    results = classifier(text)
    return results[0]['label'], results[0]['score']

# Create the Gradio interface
iface = gr.Interface(
    fn=predict_sentiment,
    inputs="text",
    outputs=["text", "number"],
    title="Sentiment Analysis",
    description="Enter text to classify its sentiment as positive or negative."
)

# Launch the interface
iface.launch()