Instructions to use tomriddle/anythinv3-vae with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use tomriddle/anythinv3-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("tomriddle/anythinv3-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
- Local Apps
- Draw Things
- DiffusionBee
- Xet hash:
- 88b832ff92e42bb1ac39dfc10e127c7faddeb14a99a11c6fef7035bdbf05a10f
- Size of remote file:
- 492 MB
- SHA256:
- 2c101a1aae1bfb4466920a366b2550e68b1088f7d6906b9e84d83d16ad772e51
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.