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Stable Diffusion
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  ---
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  ## Model Card for lyraSD
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- lyraSD is currently the **fastest Stable Diffusion model** available, boasting an inference cost of only **0.36 seconds** for a 512x512 image, accelerating the process up to **10 times faster** than the original version.
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  Among its main features are:
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@@ -28,8 +28,8 @@ Among its main features are:
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  - device: Nvidia A100 40G
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  - img size: 512x512
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  - percision:fp16
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- - steps: 20
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- - solver: EularA
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  ### text2img
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  |model|time cost(ms)|memory(MB)|
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  ```python
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  from lyraSD import LyraSD
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- t2imodel = LyraSD("text2img", "./sd1.5-engine")
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  t2imodel.inference(prompt="A fantasy landscape, trending on artstation", use_super=False)
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  from PIL import Image
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- i2imodel = LyraSD("img2img", "./sd1.5-engine")
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  demo_img = Image.open("output/text2img_demo.jpg")
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  i2imodel.inference(prompt="A fantasy landscape, trending on artstation", image=demo_img)
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  ---
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  ## Model Card for lyraSD
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+ lyraSD is currently the **fastest Stable Diffusion model** available, boasting an inference cost of only **0.435 seconds** for a 512x512 image, accelerating the process up to **10 times faster** than the original version.
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  Among its main features are:
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  - device: Nvidia A100 40G
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  - img size: 512x512
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  - percision:fp16
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+ - steps: 30
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+ - solver: LMSD
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  ### text2img
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  |model|time cost(ms)|memory(MB)|
 
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  ```python
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  from lyraSD import LyraSD
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+ t2imodel = LyraSD("text2img", "./sd1.4-engine")
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  t2imodel.inference(prompt="A fantasy landscape, trending on artstation", use_super=False)
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  from PIL import Image
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+ i2imodel = LyraSD("img2img", "./sd1.4-engine")
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  demo_img = Image.open("output/text2img_demo.jpg")
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  i2imodel.inference(prompt="A fantasy landscape, trending on artstation", image=demo_img)
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