app.py

import gradio as gr
from transformers import pipeline, AutoModelForCausalLM, AutoTokenizer

# Load model and tokenizer
model_name = "gpt2"
model = AutoModelForCausalLM.from_pretrained(model_name)
tokenizer = AutoTokenizer.from_pretrained(model_name)

# Define pipeline for text generation
generator = pipeline('text-generation', model=model, tokenizer=tokenizer)

# Define Gradio interface
def generate_text(prompt):
    result = generator(prompt, max_length=50)[0]
    generated_text = result['generated_text']
    return generated_text

iface = gr.Interface(fn=generate_text, inputs="text", outputs="text", 
                     title="Text Generation with Hugging Face and Gradio", 
                     description="Enter prompt to generate text.")

# Launch Gradio interface
iface.launch()