app.py

import gradio as gr
from transformers import pipeline

# Load a pre-trained text classification model from Hugging Face
classifier = pipeline("sentiment-analysis", model="distilbert-base-uncased-finetuned-sst-2-english")

def classify_text(text):
    # Classify the input text
    result = classifier(text)
    return result[0]['label']

# Define the Gradio interface
iface = gr.Interface(
    fn=classify_text,
    inputs=gr.Textbox(lines=2, placeholder="Enter text here..."),
    outputs=gr.Textbox(),
    title="Text Classification",
    description="Classify text into positive or negative sentiment using Hugging Face Transformers."
)

# Launch the interface
if __name__ == "__main__":
    iface.launch()