Instructions to use ByteDance/SDXL-Lightning with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use ByteDance/SDXL-Lightning with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("ByteDance/SDXL-Lightning", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
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## Demos
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* Generate with all configurations, best quality: [Demo](https://huggingface.co/spaces/ByteDance/SDXL-Lightning)
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* Real-time generation as you type, lightning-fast: [Demo from fastsdxl.ai](https://fastsdxl.ai/)
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## Checkpoints
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## Demos
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* Generate with all configurations, best quality: [Demo](https://huggingface.co/spaces/ByteDance/SDXL-Lightning)
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## Checkpoints
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