Instructions to use AiArtLab/sdxs-1b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use AiArtLab/sdxs-1b with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("AiArtLab/sdxs-1b", dtype=torch.bfloat16, device_map="cuda") prompt = "sdxs-1b" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
2601
Browse files- pipeline_sdxs.py +1 -1
- samples/unet_576x640_0.jpg +2 -2
- samples/unet_608x640_0.jpg +2 -2
- samples/unet_640x416_0.jpg +2 -2
- samples/unet_640x448_0.jpg +2 -2
- samples/unet_640x544_0.jpg +2 -2
- samples/unet_640x576_0.jpg +2 -2
- samples/unet_640x608_0.jpg +2 -2
- samples/unet_640x640_0.jpg +2 -2
pipeline_sdxs.py
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@@ -200,7 +200,7 @@ class SdxsPipeline(DiffusionPipeline):
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generator: Optional[torch.Generator] = None,
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output_type: str = "pil",
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return_dict: bool = True,
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structure_preservation: float = 0.
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**kwargs,
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):
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device = self.device
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generator: Optional[torch.Generator] = None,
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output_type: str = "pil",
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return_dict: bool = True,
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structure_preservation: float = 0.2, # Новый параметр: сохранение структуры 0-1
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**kwargs,
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):
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device = self.device
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samples/unet_576x640_0.jpg
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