Instructions to use nyanko7/sdxl-vae-0.9 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use nyanko7/sdxl-vae-0.9 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("nyanko7/sdxl-vae-0.9", 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
Download sdxl-vae-0.9.ckpt from nyanko7/sdxl-vae-0.9: direct link, hf CLI and curl.
- Browser
- Download file 335 MB
-
https://huggingface.co/nyanko7/sdxl-vae-0.9/resolve/main/sdxl-vae-0.9.ckpt
- Command line
-
hf download hf://nyanko7/sdxl-vae-0.9/sdxl-vae-0.9.ckpt
-
curl -L -o sdxl-vae-0.9.ckpt https://huggingface.co/nyanko7/sdxl-vae-0.9/resolve/main/sdxl-vae-0.9.ckpt
335 MB
- Xet hash:
- bc672b9a2fa5053016f6bc0049c24836977616eb2a991cc8f704427fd5fc79b5
- Size of remote file:
- 335 MB
- SHA256:
- 60931633d786ca36a1f811a45c8941cffa5cd6cb576969836ea4b8ab6b00793a
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