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from diffusers import StableDiffusionXLPipeline
import torch
from gradio import Interface, Image, Dropdown, Slider
import gradio as gr
import spaces
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=[
["very pretty naked Japanese 18 yo girl, looking at the viewer, ashamed, (smile:0.7), textured fair skin, perfect teen body, medium breasts"],
],
cache_examples=False,
theme=gr.themes.Soft()
)
gradio_interface.launch() |