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
- Xet hash:
- cc03fb4a4e058731b1dd2b487cbca7e6d565518e2e1d72c9912624168f3fcb44
- Size of remote file:
- 167 MB
- SHA256:
- 2d63d2785d749be36f552012f1ad4902e0a18e473750e89e66d493781d00bdf1
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