Instructions to use AiArtLab/sdxl_vae with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use AiArtLab/sdxl_vae 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/sdxl_vae", 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
nightly
Browse files- README.md +8 -6
- samples/sample_0.jpg +2 -2
- samples/sample_1.jpg +2 -2
- samples/sample_2.jpg +2 -2
- samples/sample_decoded.jpg +2 -2
- vae_nightly/diffusion_pytorch_model.safetensors +1 -1
README.md
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Alchemist eval (512px)
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| madebyollin/sdxl-vae-fp16 | 100% | 100% | 100% |
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[](https://imgsli.com/NDA3OTgz)
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| Model | MSE | PSNR | LPIPS | Edge |
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| madebyollin/sdxl-vae-fp16 | 100% | 100% | 100% | 100% |
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| KBlueLeaf/EQ-SDXL-VAE | 106.2% | 99.8% | 96.5% | 97.6% |
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| AiArtLab/sdxl_vae | 111.8% | 101.7% | 106.7% | 102.3% |
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| AiArtLab/sdxlvae_nightly | 117.9% | 102.3% | 107.0% | 102.9% |
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| AiArtLab/sdxs | 321.4% | 119.5% | 263.7% | 176.4% |
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| FLUX.1-schnell-vae | 382.2% | 120.9% | 320.7% | 201.6% |
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[](https://imgsli.com/NDA3OTgz)
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