app.py

import torch
from diffusers import StableDiffusionPipeline
import gradio as gr

pipe = StableDiffusionPipeline.from_pretrained("paavansundar/image-diffusion", torch_dtype=torch.float32)
def generate_img(prompt):
    pipe.enable_attention_slicing()
    return pipe(prompt).images[0]
with gr.Blocks() as demo:
    im = gr.Image()
    prompt = gr.Textbox(label="Input", lines=2)
    btn = gr.Button(value="Generate Image")    
    btn.click(generate_img, inputs=[prompt], outputs=[im])

if __name__ == "__main__":
    demo.launch()