app.py

import gradio as gr
import spaces
import torch
from diffusers import DiffusionPipeline


@spaces.GPU()
@torch.inference_mode()
def inference(
    model_id: str,
    prompt: str,
    negative_prompt: str = "",
    progress=gr.Progress(track_tqdm=True),
):
    device = torch.device("cuda" if torch.cuda.is_available() else "cpu")

    pipe = DiffusionPipeline.from_pretrained(
        model_id,
        torch_dtype=torch.float16,
    ).to(device)

    image = pipe(
        prompt,
        negative_prompt=negative_prompt,
    ).images[0]

    return image


if __name__ == "__main__":
    demo = gr.Interface(
        fn=inference,
        inputs=[
            gr.Text(
                label="Model ID",
                value="stabilityai/stable-diffusion-3-medium-diffusers",
            ),
            gr.Text(label="Prompt", value=""),
            gr.Text(label="Negative Prompt", value=""),
        ],
        outputs=[
            gr.Image(label="Image", type="pil"),
        ],
    )
    demo.launch()