AP123 PeterL1n commited on
Commit
f2aa102
1 Parent(s): 3d2c0fd

Update app.py (#4)

Browse files

- Update app.py (d484f91b36fc1f2c9fc069a3fa9bd2f12fd28c34)


Co-authored-by: Peter Lin <PeterL1n@users.noreply.huggingface.co>

Files changed (1) hide show
  1. app.py +4 -4
app.py CHANGED
@@ -75,19 +75,19 @@ def generate_image(prompt, ckpt):
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  # Gradio Interface
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  description = """
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- This demo utilizes the SDXL-Lightning model by ByteDance, which is a fast text-to-image generative model capable of producing high-quality images in 4 steps.
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  As a community effort, this demo was put together by AngryPenguin. Link to model: https://huggingface.co/ByteDance/SDXL-Lightning
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  """
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  with gr.Blocks(css="style.css") as demo:
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- gr.HTML("<h1><center>Text-to-Image with SDXL Lightning ⚡</center></h1>")
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  gr.Markdown(description)
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  with gr.Group():
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  with gr.Row():
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  prompt = gr.Textbox(label='Enter you image prompt:', scale=8)
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- ckpt = gr.Dropdown(label='Select Inference Steps',choices=['1-Step', '2-Step', '4-Step', '8-Step'], value='4-Step', interactive=True)
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  submit = gr.Button(scale=1, variant='primary')
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- img = gr.Image(label='SDXL-Lightening Generate Image')
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  prompt.submit(fn=generate_image,
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  inputs=[prompt, ckpt],
 
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  # Gradio Interface
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  description = """
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+ This demo utilizes the SDXL-Lightning model by ByteDance, which is a lightning-fast text-to-image generative model capable of producing high-quality images in 4 steps.
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  As a community effort, this demo was put together by AngryPenguin. Link to model: https://huggingface.co/ByteDance/SDXL-Lightning
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  """
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  with gr.Blocks(css="style.css") as demo:
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+ gr.HTML("<h1><center>Text-to-Image with SDXL-Lightning ⚡</center></h1>")
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  gr.Markdown(description)
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  with gr.Group():
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  with gr.Row():
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  prompt = gr.Textbox(label='Enter you image prompt:', scale=8)
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+ ckpt = gr.Dropdown(label='Select inference steps',choices=['1-Step', '2-Step', '4-Step', '8-Step'], value='4-Step', interactive=True)
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  submit = gr.Button(scale=1, variant='primary')
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+ img = gr.Image(label='SDXL-Lightning Generated Image')
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  prompt.submit(fn=generate_image,
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  inputs=[prompt, ckpt],