Files changed (1) hide show
  1. app.py +5 -28
app.py CHANGED
@@ -5,28 +5,6 @@ from PIL import Image
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  from model import *
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- # SAFETY_CHECKER = os.environ.get("SAFETY_CHECKER", "0") == "1"
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-
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- # Constants
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- # base = "stabilityai/stable-diffusion-xl-base-1.0"
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- # repo = "ByteDance/SDXL-Lightning"
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- # checkpoints = {
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- # "1-Step" : ["sdxl_lightning_1step_unet_x0.safetensors", 1],
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- # "2-Step" : ["sdxl_lightning_2step_unet.safetensors", 2],
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- # "4-Step" : ["sdxl_lightning_4step_unet.safetensors", 4],
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- # "8-Step" : ["sdxl_lightning_8step_unet.safetensors", 8],
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- # }
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- # loaded = None
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-
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-
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- # Ensure model and scheduler are initialized in GPU-enabled function
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- # if torch.cuda.is_available():
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- # pipe = StableDiffusionXLPipeline.from_pretrained(base, torch_dtype=torch.float16, variant="fp16").to("cuda")
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-
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-
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- # Function
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- # @spaces.GPU(enable_queue=True)
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-
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  def generate_image(prompt):
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  return prompt_to_img(prompt)[0]
@@ -35,19 +13,18 @@ def generate_image(prompt):
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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 your prompt (English)', 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],
 
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  from model import *
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  def generate_image(prompt):
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  return prompt_to_img(prompt)[0]
 
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  # Gradio Interface
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  description = """
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+ This demo utilizes a specialized variant of the Stable Diffusion model designed for multilingual text-to-image synthesis. In response to the observed underperformance of existing models on languages beyond English, this project introduces the Multilingual Stable Diffusion, providing a more inclusive solution for diverse linguistic contexts.
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+ Link to Github repo: https://github.com/NajlaaNawaii/Multilingual-Stable-Diffusion-Towards-more-Inclusive-Text-To-Image-Synthesis
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  """
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  with gr.Blocks(css="style.css") as demo:
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+ gr.HTML("<h1><center>Multilingual Stable Diffusion 🧨</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 your prompt', scale=8)
 
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  submit = gr.Button(scale=1, variant='primary')
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+ img = gr.Image(label='Generated Image')
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  prompt.submit(fn=generate_image,
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  inputs=[prompt],