# Thanks: https://huggingface.co/spaces/markmagic/Stable-Diffusion-3/blob/main/app.py import os import random import uuid import gradio as gr import numpy as np from PIL import Image import spaces import torch from diffusers import StableDiffusion3Pipeline, DPMSolverMultistepScheduler, AutoencoderKL DESCRIPTION = """# 日本語で入力できるStable Diffusion 3""" pipe = StableDiffusion3Pipeline.from_pretrained( "stabilityai/stable-diffusion-3-medium-diffusers", torch_dtype=torch.float16, token=os.getenv("TOKEN") ) @spaces.GPU() def generate( prompt: str, negative_prompt: str = "", seed: int = 0, width: int = 1024, height: int = 1024, guidance_scale: float = 7, num_inference_steps=30, progress=gr.Progress(track_tqdm=True), ): pipe = pipe.to("cuda") generator = torch.Generator().manual_seed(seed) output = pipe( prompt=prompt, negative_prompt=negative_prompt, width=width, height=height, guidance_scale=guidance_scale, num_inference_steps=num_inference_steps, generator=generator, output_type="pil", ).images return output examples = [ "A red sofa on top of a white building.", ] css = ''' .gradio-container{max-width: 1000px !important} h1{text-align:center} ''' with gr.Blocks(css=css) as demo: with gr.Row(): with gr.Column(): gr.HTML( """

日本語で入力できるStable Diffusion 3 Medium

""" ) gr.HTML( """ """ ) with gr.Group(): 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.Gallery(label="Result", elem_id="gallery", show_label=False) with gr.Accordion("Advanced options", open=False): with gr.Row(): negative_prompt = gr.Text( label="Negative prompt", max_lines=1, value = "deformed, distorted, disfigured, poorly drawn, bad anatomy, wrong anatomy, extra limb, missing limb, floating limbs, mutated hands and fingers, disconnected limbs, mutation, mutated, ugly, disgusting, blurry, amputation, NSFW", visible=True, ) seed = gr.Slider( label="Seed", minimum=0, maximum=MAX_SEED, step=1, value=0, ) steps = gr.Slider( label="Steps", minimum=0, maximum=60, step=1, value=30, ) with gr.Row(): guidance_scale = gr.Slider( label="Guidance Scale", minimum=0.1, maximum=10, step=0.1, value=7.0, ) gr.Examples( examples=examples, inputs=prompt, outputs=[result], fn=generate, cache_examples=CACHE_EXAMPLES, ) gr.on( triggers=[ prompt.submit, negative_prompt.submit, run_button.click, ], fn=generate, inputs=[ prompt, negative_prompt, seed, guidance_scale, steps, ], outputs=[result], ) if __name__ == "__main__": demo.queue().launch()