Instructions to use ostris/vae-kl-f8-d16 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use ostris/vae-kl-f8-d16 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("ostris/vae-kl-f8-d16", 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
Request: DOI
#5
by jlin3 - opened
Hi, I'm conducting research using VAE's to avoid watermark detection and have used your model as an example of using a VAE with slightly altered architecture. Is there a preferred way you would want this model to be cited as (currently I'm just citing your model as a URL)?