Instructions to use AdamOswald1/Ultima-Waifu-Diffusion with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use AdamOswald1/Ultima-Waifu-Diffusion with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("AdamOswald1/Ultima-Waifu-Diffusion", 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 Settings
- Draw Things
- DiffusionBee
Download AnimeChanStyle-v2.zip from AdamOswald1/Ultima-Waifu-Diffusion: direct link, hf CLI and curl.
- Browser
- Download file 99 MB
-
https://huggingface.co/AdamOswald1/Ultima-Waifu-Diffusion/resolve/main/AnimeChanStyle-v2.zip
- Command line
-
hf download hf://AdamOswald1/Ultima-Waifu-Diffusion/AnimeChanStyle-v2.zip
-
curl -L -o AnimeChanStyle-v2.zip https://huggingface.co/AdamOswald1/Ultima-Waifu-Diffusion/resolve/main/AnimeChanStyle-v2.zip
99 MB
- Xet hash:
- e0be1075ca38afa4db3a94818342e315b3a9119a469e5d3529b88a7676f94353
- Size of remote file:
- 99 MB
- SHA256:
- 09f5678e615988ce35d01ce9980a546568e27ec52065d2578c265275b070ea27
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.