Lawrence-cj commited on
Commit
227fc7d
1 Parent(s): a731861

update app.py

Browse files
Files changed (1) hide show
  1. app.py +3 -2
app.py CHANGED
@@ -7,7 +7,7 @@ import uuid
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  import gradio as gr
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  import numpy as np
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  import uuid
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- from diffusers import PixArtAlphaPipeline, LatentConsistencyModelPipeline, LCMScheduler
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  import torch
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  from typing import Tuple
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  from datetime import datetime
@@ -19,6 +19,7 @@ DESCRIPTION = """![Logo](https://raw.githubusercontent.com/PixArt-alpha/PixArt-a
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  #### [LCMs](https://github.com/luosiallen/latent-consistency-model) is a diffusion distillation method which predict PF-ODE's solution directly in latent space, achieving super fast inference with few steps.
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  #### English prompts ONLY; 提示词仅限英文
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  ### <span style='color: red;'> Don't want to queue or Don't get satisfied results? Try original demo: [PixArt-alpha](https://huggingface.co/spaces/PixArt-alpha/PixArt-alpha) [OpenXLab](https://openxlab.org.cn/apps/detail/PixArt-alpha/PixArt-alpha) or [Google Colab Demo](https://colab.research.google.com/drive/1jZ5UZXk7tcpTfVwnX33dDuefNMcnW9ME?usp=sharing).
 
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  """
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  if not torch.cuda.is_available():
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  DESCRIPTION += "\n<p>Running on CPU 🥶 This demo does not work on CPU.</p>"
@@ -250,7 +251,7 @@ with gr.Blocks(css="style.css") as demo:
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  minimum=1,
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  maximum=30,
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  step=1,
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- value=4,
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  )
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  gr.Examples(
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  examples=examples,
 
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  import gradio as gr
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  import numpy as np
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  import uuid
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+ from diffusers import PixArtAlphaPipeline, LCMScheduler
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  import torch
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  from typing import Tuple
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  from datetime import datetime
 
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  #### [LCMs](https://github.com/luosiallen/latent-consistency-model) is a diffusion distillation method which predict PF-ODE's solution directly in latent space, achieving super fast inference with few steps.
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  #### English prompts ONLY; 提示词仅限英文
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  ### <span style='color: red;'> Don't want to queue or Don't get satisfied results? Try original demo: [PixArt-alpha](https://huggingface.co/spaces/PixArt-alpha/PixArt-alpha) [OpenXLab](https://openxlab.org.cn/apps/detail/PixArt-alpha/PixArt-alpha) or [Google Colab Demo](https://colab.research.google.com/drive/1jZ5UZXk7tcpTfVwnX33dDuefNMcnW9ME?usp=sharing).
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+ ### Feel free to change LCM inference steps in range [4, 10] according to your needs.
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  """
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  if not torch.cuda.is_available():
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  DESCRIPTION += "\n<p>Running on CPU 🥶 This demo does not work on CPU.</p>"
 
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  minimum=1,
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  maximum=30,
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  step=1,
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+ value=6,
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  )
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  gr.Examples(
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  examples=examples,