Instructions to use Anzhc/Anzhcs-VAEs with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Anzhc/Anzhcs-VAEs with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Anzhc/Anzhcs-VAEs", 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
File size: 266 Bytes
f547e7d c05ce0d 92462c6 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 | ---
license: openrail
library_name: diffusers
base_model:
- stabilityai/sdxl-vae
---
(Nothing here for now)
## Support
If you want to support me, feel free to donate on ko-fi:
https://ko-fi.com/anzhc
Or send me some BTC:
bc1qpc5kmxrpqp6x8ykdu6976s4rvsz0utk22h80j9 |