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Files changed (28) hide show
  1. README.md +14 -10
  2. media/result_grid.jpg +2 -2
  3. media/result_grid_base.jpg +3 -0
  4. samples/unet_320x640_0.jpg +2 -2
  5. samples/unet_352x640_0.jpg +2 -2
  6. samples/unet_384x640_0.jpg +2 -2
  7. samples/unet_416x640_0.jpg +2 -2
  8. samples/unet_448x640_0.jpg +2 -2
  9. samples/unet_480x640_0.jpg +2 -2
  10. samples/unet_512x640_0.jpg +2 -2
  11. samples/unet_544x640_0.jpg +2 -2
  12. samples/unet_576x640_0.jpg +2 -2
  13. samples/unet_608x640_0.jpg +2 -2
  14. samples/unet_640x320_0.jpg +2 -2
  15. samples/unet_640x352_0.jpg +2 -2
  16. samples/unet_640x384_0.jpg +2 -2
  17. samples/unet_640x416_0.jpg +2 -2
  18. samples/unet_640x448_0.jpg +2 -2
  19. samples/unet_640x480_0.jpg +2 -2
  20. samples/unet_640x512_0.jpg +2 -2
  21. samples/unet_640x544_0.jpg +2 -2
  22. samples/unet_640x576_0.jpg +2 -2
  23. samples/unet_640x608_0.jpg +2 -2
  24. samples/unet_640x640_0.jpg +2 -2
  25. test.ipynb +2 -2
  26. text_encoder/model.safetensors +2 -2
  27. unet/diffusion_pytorch_model.safetensors +2 -2
  28. vae/diffusion_pytorch_model.safetensors +2 -2
README.md CHANGED
@@ -8,14 +8,16 @@ datasets:
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  # Simple Diffusion XS
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  *XS Size, Excess Quality*
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-
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  At AiArtLab, we strive to create a free, compact and fast model that can be trained on consumer graphics cards.
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- - Model: 0.8b parameters [stable-diffusion unet](https://huggingface.co/CompVis/stable-diffusion-v1-4)
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- - Text encoder: [LongCLIP with 248 tokens](https://huggingface.co/zer0int/CLIP-KO-LITE-TypoAttack-Attn-Dropout-ViT-L-14)
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- - VAE: 16x16ch, Simple VAE
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-
 
 
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  ![promo](media/result_grid.jpg)
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  ### Example
@@ -27,7 +29,7 @@ from diffusers import DiffusionPipeline
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  device = "cuda" if torch.cuda.is_available() else "cpu"
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  dtype = torch.float16 if torch.cuda.is_available() else torch.float32
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- pipe_id = "AiArtLab/sdxs-08b"
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  pipe = DiffusionPipeline.from_pretrained(
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  pipe_id,
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  torch_dtype=dtype,
@@ -59,10 +61,12 @@ image.show(image)
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  ## Donations
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  Please contact with us if you may provide some GPU's or money on training
 
 
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- DOGE: DEw2DR8C7BnF8GgcrfTzUjSnGkuMeJhg83
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-
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- BTC: 3JHv9Hb8kEW8zMAccdgCdZGfrHeMhH1rpN
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  ## Contacts
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@@ -76,7 +80,7 @@ mail at aiartlab.org (slow response)
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  @misc{sdxs,
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  title={Simple Diffusion XS},
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  author={recoilme with help of AiArtLab Team},
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- url={https://huggingface.co/AiArtLab/sdxs-08b},
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  year={2026}
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  }
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  ```
 
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  # Simple Diffusion XS
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  *XS Size, Excess Quality*
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+ ![promo](media/result_grid_base.jpg)
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  At AiArtLab, we strive to create a free, compact and fast model that can be trained on consumer graphics cards.
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+ - Unet: 1.16b parameters
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+ - Clip: [LongCLIP with 248 tokens](https://huggingface.co/zer0int/CLIP-KO-LITE-TypoAttack-Attn-Dropout-ViT-L-14)
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+ - VAE: 16ch-16x(8x-enc/16x-decoder)
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+ - Sampling: 100%|██████████| 40/40 [00:01<00:00, 30.72it/s] (1024x1280)
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+
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+ ### Random samples
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  ![promo](media/result_grid.jpg)
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  ### Example
 
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  device = "cuda" if torch.cuda.is_available() else "cpu"
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  dtype = torch.float16 if torch.cuda.is_available() else torch.float32
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+ pipe_id = "AiArtLab/sdxs-1b"
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  pipe = DiffusionPipeline.from_pretrained(
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  pipe_id,
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  torch_dtype=dtype,
 
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  ## Donations
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  Please contact with us if you may provide some GPU's or money on training
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+ - [recoilme](https://t.me/recoilme) *prefered way
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+ - mail at aiartlab.org (slow response)
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+ - Rubles: [For users from Russia](https://www.tbank.ru/cf/90ensBQqpJj)
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+ - DOGE: DEw2DR8C7BnF8GgcrfTzUjSnGkuMeJhg83
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+ - BTC: 3JHv9Hb8kEW8zMAccdgCdZGfrHeMhH1rpN
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  ## Contacts
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  @misc{sdxs,
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  title={Simple Diffusion XS},
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  author={recoilme with help of AiArtLab Team},
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+ url={https://huggingface.co/AiArtLab/sdxs-1b},
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  year={2026}
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  }
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  ```
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