app.py

import gradio as gr
from transformers import pipeline

# Load the BigGAN model using the transformers pipeline
generator = pipeline("text-to-image", model="osanseviero/BigGAN-deep-128")

def generate_image(text_input):
    """Generates an image from text using the BigGAN pipeline."""
    # The pipeline's output is an image.
    image = generator(text_input)["images"][0]
    return image

# Create the Gradio interface directly
interface = gr.Interface(
    fn=generate_image,
    inputs=gr.Textbox(label="Enter a prompt"),
    outputs=gr.Image(label="Generated Image"),
    title="BigGAN ImageNet",
    description="BigGAN text-to-image demo.",
    examples=[["american robin"], ["ocean sunset"], ["cat in a hat"]]
)

interface.launch()