import gradio as gr import spaces from panna import SD3 model = SD3("stabilityai/stable-diffusion-3-medium-diffusers") title = ("# [Stable Diffusion 3 Medium](https://huggingface.co/stabilityai/stable-diffusion-3-medium)\n" "The demo is part of [panna](https://github.com/abacws-abacus/panna) project.") examples = [ "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k", "A female model, high quality, fashion, Paris, Vogue, Maison Margiela, 8k", ] css = """ #col-container { margin: 0 auto; max-width: 580px; } """ @spaces.GPU def infer(prompt, negative_prompt, seed, width, height, guidance_scale, num_inference_steps): return model.text2image( prompt=[prompt], negative_prompt=[negative_prompt], guidance_scale=guidance_scale, num_inference_steps=num_inference_steps, width=width, height=height, seed=seed )[0] with gr.Blocks(css=css) as demo: with gr.Column(elem_id="col-container"): gr.Markdown(title) with gr.Row(): prompt = gr.Text(label="Prompt", show_label=False, max_lines=1, placeholder="Enter your prompt", container=False) run_button = gr.Button("Run", scale=0) result = gr.Image(label="Result", show_label=False) with gr.Accordion("Advanced Settings", open=False): negative_prompt = gr.Text(label="Negative Prompt", max_lines=1, placeholder="Enter a negative prompt") seed = gr.Slider(label="Seed", minimum=0, maximum=1_000_000, step=1, value=0) with gr.Row(): width = gr.Slider(label="Width", minimum=256, maximum=1344, step=64, value=1024) height = gr.Slider(label="Height", minimum=256, maximum=1344, step=64, value=1024) with gr.Row(): guidance_scale = gr.Slider(label="Guidance scale", minimum=0.0, maximum=10.0, step=0.1, value=7.5) num_inference_steps = gr.Slider(label="Inference steps", minimum=1, maximum=50, step=1, value=50) gr.Examples(examples=examples, inputs=[prompt]) gr.on( triggers=[run_button.click, prompt.submit, negative_prompt.submit], fn=infer, inputs=[prompt, negative_prompt, seed, width, height, guidance_scale, num_inference_steps], outputs=[result] ) demo.launch(server_name="0.0.0.0")