app.py

from diffusers import StableDiffusionXLPipeline
import torch
from gradio import Interface, Image
import gradio as gr
import spaces

model_id = "RunDiffusion/Juggernaut-X-v10"
pipe = StableDiffusionXLPipeline.from_pretrained(model_id, torch_dtype=torch.float16)
pipe = pipe.to("cuda")

@spaces.GPU()
def text_to_image(prompt, progress=gr.Progress(track_tqdm=True)):
 image = pipe(prompt).images [0]
 return image


gradio_interface = Interface(
 fn=text_to_image,
 inputs="text",
 outputs=Image(type="pil", show_download_button=True),
 examples=[["person running"]],
 theme=gr.themes.Soft()
)
gradio_interface.launch()