import spaces from diffusers import StableDiffusionXLPipeline import torch from gradio import Interface, Image, Dropdown, Slider import gradio as gr model_id = "RunDiffusion/Juggernaut-X-v10" pipe = StableDiffusionXLPipeline.from_pretrained(model_id, torch_dtype=torch.float16) pipe = pipe.to("cuda") @spaces.GPU() def text_to_image(prompt, negative_prompt, steps, guidance_scale, add_4k_masterpiece, progress=gr.Progress(track_tqdm=True)): if add_4k_masterpiece: prompt += ", 4k, (masterpiece)" image = pipe(prompt, negative_prompt=negative_prompt, num_inference_steps=steps, guidance_scale=guidance_scale).images[0] return image duplicate_button = gr.DuplicateButton(value="Duplicate Space for private use", elem_id="duplicate-button") gradio_interface = Interface( fn=text_to_image, allow_duplication=True, inputs=[ gr.Textbox(label="Prompt", lines=2, placeholder="Enter your prompt here..."), gr.Textbox(label="Negative Prompt", lines=2, placeholder="What to exclude from the image..."), gr.Slider(minimum=1, maximum=65, value=50, label="Steps", step=1), gr.Slider(minimum=1, maximum=20, value=7.5, label="Guidance Scale", step=0.1), gr.Checkbox(label="Add recommended prompt items (4k, masterpiece)", value=False) ], outputs=Image(type="pil", show_download_button=True), examples=[ ["magical kitten, 4k, high quality, (masterpiece)"], ], cache_examples=False, theme=gr.themes.Soft() ) gradio_interface.launch()