Instructions to use JosephusCheung/RuminationDiffusion with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use JosephusCheung/RuminationDiffusion with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("JosephusCheung/RuminationDiffusion", dtype=torch.bfloat16, device_map="cuda") prompt = "masterpiece, best quality, anime, 1girl, brown hair, green eyes, colorful, autumn, cumulonimbus clouds, lighting, blue sky, garden, looking at viewer" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Download vae/diffusion_pytorch_model.bin from JosephusCheung/RuminationDiffusion: direct link, hf CLI and curl.
- Browser
- Download file 335 MB
-
https://huggingface.co/JosephusCheung/RuminationDiffusion/resolve/22bcc9043c19008e2de27dca0752ef57af95df65/vae/diffusion_pytorch_model.bin
- Command line
-
hf download hf://JosephusCheung/RuminationDiffusion@22bcc9043c19008e2de27dca0752ef57af95df65/vae/diffusion_pytorch_model.bin
-
curl -L -o diffusion_pytorch_model.bin https://huggingface.co/JosephusCheung/RuminationDiffusion/resolve/22bcc9043c19008e2de27dca0752ef57af95df65/vae/diffusion_pytorch_model.bin
335 MB
- Xet hash:
- 778dc1c69347ac5285006812c018bacd75f3c015b0a876314d6c5878ba554169
- Size of remote file:
- 335 MB
- SHA256:
- 36bb8e1b54aba3a0914eb35fba13dcb107e9f18d379d1df2158732cd4bf56a94
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