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.safetensors 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/4fe0dd60b747b422424b1a0c221ba63fbd1dc550/sdxl-vae-0.9.safetensors
- Command line
-
hf download hf://nyanko7/sdxl-vae-0.9@4fe0dd60b747b422424b1a0c221ba63fbd1dc550/sdxl-vae-0.9.safetensors
-
curl -L -o sdxl-vae-0.9.safetensors https://huggingface.co/nyanko7/sdxl-vae-0.9/resolve/4fe0dd60b747b422424b1a0c221ba63fbd1dc550/sdxl-vae-0.9.safetensors
335 MB
- Xet hash:
- bbd1f42479e6ab92792c47958fa557350332fd92b0643cb9f796c419efad4d38
- Size of remote file:
- 335 MB
- SHA256:
- d85de3e994bdcbd928b025b312b7890e328b0b8058be07f6e0dcb1b9b66520ec
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