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license: apache-2.0
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pipeline_tag: text-to-image
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# Simple Diffusion XS
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*XS Size, Excess Quality*
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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: 1.5b parameters
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- Text encoder: Qwen3 (0.6B parameters)
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- VAE: 8x16ch, [Simple VAE](https://huggingface.co/AiArtLab/simplevae)
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The model was trained for ~3 months on (2-4)x RTX 5090 GPUs using over 1+ million images of various resolutions and styles, primarily anime and illustrations.
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[Gradio](https://sdxs.aiartlab.org/)
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### Example
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```
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import torch
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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"
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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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trust_remote_code=True
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).to(device)
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prompt = "girl, smiling, red eyes, blue hair, white shirt"
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negative_prompt="low quality, bad quality"
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image = pipe(
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prompt=prompt,
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negative_prompt = negative_prompt,
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).images[0]
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image.show(image)
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```
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### Model Limitations:
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- Limited concept coverage due to the small dataset.
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## Acknowledgments
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- **[Stan](https://t.me/Stangle)** — Key investor. Thank you for believing in us when others called it madness.
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- **Captainsaturnus**
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- **Love. Death. Transformers.**
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- **TOPAPEC**
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## Datasets
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- **[CaptionEmporium](https://huggingface.co/CaptionEmporium)**
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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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BTC: 3JHv9Hb8kEW8zMAccdgCdZGfrHeMhH1rpN
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## Contacts
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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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## More examples
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## Citation
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```bibtex
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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},
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year={2025}
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}
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```
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