Running on CPU 🥶 This demo may not work on CPU.
" MAX_SEED = np.iinfo(np.int32).max CACHE_EXAMPLES = False MAX_IMAGE_SIZE = int(os.getenv("MAX_IMAGE_SIZE", "1536")) USE_TORCH_COMPILE = False ENABLE_CPU_OFFLOAD = os.getenv("ENABLE_CPU_OFFLOAD", "0") == "1" device = torch.device("cuda:0" if torch.cuda.is_available() else "cpu") def load_pipeline(): model_id = "stabilityai/stable-diffusion-3-medium-diffusers" pipe = StableDiffusion3Pipeline.from_pretrained( model_id, #device_map="balanced", torch_dtype=torch.float16 ) return pipe aspect_ratios = { "21:9": (21, 9), "2:1": (2, 1), "16:9": (16, 9), "5:4": (5, 4), "4:3": (4, 3), "3:2": (3, 2), "1:1": (1, 1), } # Function to calculate resolution def calculate_resolution(aspect_ratio, mode='landscape', total_pixels=1024*1024, divisibility=64): if aspect_ratio not in aspect_ratios: raise ValueError(f"Invalid aspect ratio: {aspect_ratio}") width_multiplier, height_multiplier = aspect_ratios[aspect_ratio] ratio = width_multiplier / height_multiplier if mode == 'portrait': # Swap the ratio for portrait mode ratio = 1 / ratio height = int((total_pixels / ratio) ** 0.5) height -= height % divisibility width = int(height * ratio) width -= width % divisibility while width * height > total_pixels: height -= divisibility width = int(height * ratio) width -= width % divisibility return width, height def save_image(img): unique_name = str(uuid.uuid4()) + ".png" img.save(unique_name) return unique_name def randomize_seed_fn(seed: int, randomize_seed: bool) -> int: if randomize_seed: seed = random.randint(0, MAX_SEED) return seed @spaces.GPU def generate( prompt:str, negative_prompt: str = "", use_negative_prompt: bool = False, seed: int = 0, aspect: str = "1:1", mode: str = "landscape", guidance_scale: float = 7.5, randomize_seed: bool = False, num_inference_steps=30, NUM_IMAGES_PER_PROMPT=1, use_resolution_binning: bool = True, progress=gr.Progress(track_tqdm=True), ): pipe = load_pipeline() pipe.to(device) seed = int(randomize_seed_fn(seed, randomize_seed)) generator = torch.Generator().manual_seed(seed) if not use_negative_prompt: negative_prompt = None # type: ignore width, height = calculate_resolution(aspect, mode) output = pipe( prompt=prompt, negative_prompt=negative_prompt, width=width, height=height, guidance_scale=guidance_scale, num_inference_steps=num_inference_steps, generator=generator, num_images_per_prompt=NUM_IMAGES_PER_PROMPT, output_type="pil", ).images return output examples = [ "Beautiful pixel art of a wizard with hovering text \"Achievement unlocked: Diffusion models can spell now\"", "Frog sitting in a 1950s diner wearing a leather jacket and a top hat. on the table a giant burger and a small sign that says \"froggy fridays\"", "This dreamlike digital art capture a vibrant kaleidoscopic bird in a rainforest", "pair of shoes made of dried fruit skins, 3d render, bright colours, clean composition, beautiful artwork, logo saying \"SD3 rocks!\"", "post-apocalyptic city wasteland, the most delicate beautiful flower with green leaves growing from dust and rubble, vibrant colours, cinematic", "a dark-armored warrior with ornate golden details, cloaked in a flowing black cape, wielding a radiant, fiery sword, standing amidst an ominous cloudy backdrop with dramatic lighting, exuding a menacing, powerful presence.", "A wise old wizard with a long white beard, flowing robes, and a gnarled staff, casting a spell, photorealistic style", "Design a film poster for a noir thriller set in 1940s Los Angeles, featuring a shadowy figure under a streetlamp and a foggy, mysterious ambiance.", ] 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( """