Instructions to use AuraDiffusion/16ch-vae with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use AuraDiffusion/16ch-vae with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("AuraDiffusion/16ch-vae", 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:
- ffff82e86766b9aa4bfc68796722bec06a646b94025deead88437bc6655ef05b
- Size of remote file:
- 327 MB
- SHA256:
- ead97b12214d10d347a57425f2387242710c8e101e09466bcf91bc0f28d65e9c
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