app2.py

import gradio as gr
from transformers import pipeline

# Load a pre-trained text generation model from Hugging Face
generator = pipeline('text-generation', model='gpt2')

def generate_text(prompt):
    # Generate text using the model
    result = generator(prompt, max_length=100, num_return_sequences=1)
    return result[0]['generated_text']

# Create a Gradio interface
interface = gr.Interface(fn=generate_text, inputs="text", outputs="text", title="Text Generator", description="Enter a prompt to generate text.")

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