superlazycoder/zeroGPU

1import gradio as gr2import numpy as np3import random4from diffusers import DiffusionPipeline5import torch6import spaces7 8device = "cuda"9 10 11MAX_SEED = np.iinfo(np.int32).max12MAX_IMAGE_SIZE = 102413 14@spaces.GPU15def infer(prompt, negative_prompt, seed, randomize_seed, width, height, guidance_scale, num_inference_steps):16 17    if randomize_seed:18        seed = random.randint(0, MAX_SEED)19        20    generator = torch.Generator().manual_seed(seed)21    pipe = DiffusionPipeline.from_pretrained("stabilityai/sdxl-turbo", torch_dtype=torch.float16, variant="fp16", use_safetensors=True)22    pipe.enable_xformers_memory_efficient_attention()23    pipe = pipe.to(device)24    25    image = pipe(26        prompt = prompt, 27        negative_prompt = negative_prompt,28        guidance_scale = guidance_scale, 29        num_inference_steps = num_inference_steps, 30        width = width, 31        height = height,32        generator = generator33    ).images[0] 34    35    return image36 37examples = [38    "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k",39    "An astronaut riding a green horse",40    "A delicious ceviche cheesecake slice",41]42 43css="""44#col-container {45    margin: 0 auto;46    max-width: 520px;47}48"""49 50 51power_device = "GPU"52 53with gr.Blocks(css=css) as demo:54    55    with gr.Column(elem_id="col-container"):56        gr.Markdown(f"""57        # ZeroGPU Text-to-Image Gradio Template58        Currently running on {power_device}.59        """)60        61        with gr.Row():62            63            prompt = gr.Text(64                label="Prompt",65                show_label=False,66                max_lines=1,67                placeholder="Enter your prompt",68                container=False,69            )70            71            run_button = gr.Button("Run", scale=0)72        73        result = gr.Image(label="Result", show_label=False)74 75        with gr.Accordion("Advanced Settings", open=False):76            77            negative_prompt = gr.Text(78                label="Negative prompt",79                max_lines=1,80                placeholder="Enter a negative prompt",81                visible=False,82            )83            84            seed = gr.Slider(85                label="Seed",86                minimum=0,87                maximum=MAX_SEED,88                step=1,89                value=0,90            )91            92            randomize_seed = gr.Checkbox(label="Randomize seed", value=True)93            94            with gr.Row():95                96                width = gr.Slider(97                    label="Width",98                    minimum=256,99                    maximum=MAX_IMAGE_SIZE,100                    step=32,101                    value=512,102                )103                104                height = gr.Slider(105                    label="Height",106                    minimum=256,107                    maximum=MAX_IMAGE_SIZE,108                    step=32,109                    value=512,110                )111            112            with gr.Row():113                114                guidance_scale = gr.Slider(115                    label="Guidance scale",116                    minimum=0.0,117                    maximum=10.0,118                    step=0.1,119                    value=0.0,120                )121                122                num_inference_steps = gr.Slider(123                    label="Number of inference steps",124                    minimum=1,125                    maximum=12,126                    step=1,127                    value=2,128                )129        130        gr.Examples(131            examples = examples,132            inputs = [prompt]133        )134 135    run_button.click(136        fn = infer,137        inputs = [prompt, negative_prompt, seed, randomize_seed, width, height, guidance_scale, num_inference_steps],138        outputs = [result]139    )140 141demo.queue().launch()