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:
- ef7c634424973e40d4363e8d062f0a977471a07f326e1ffae97cdaa30dfb31a4
- Size of remote file:
- 167 MB
- SHA256:
- 19ab2bc029d0b1e4ce5000e370d2e1a8998b4f3be202d06ed670bbcb77cb89c1
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