Instructions to use diffusionai/diffusionbrush with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use diffusionai/diffusionbrush with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("diffusionai/diffusionbrush", 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 vae/diffusion_pytorch_model.bin from diffusionai/diffusionbrush: direct link, hf CLI and curl.
- Browser
- Download file 335 MB
-
https://huggingface.co/diffusionai/diffusionbrush/resolve/main/vae/diffusion_pytorch_model.bin
- Command line
-
hf download hf://diffusionai/diffusionbrush/vae/diffusion_pytorch_model.bin
-
curl -L -o diffusion_pytorch_model.bin https://huggingface.co/diffusionai/diffusionbrush/resolve/main/vae/diffusion_pytorch_model.bin
335 MB
- Xet hash:
- b8a27fe9d19fcac6bbd674f45155ff3e63f7a9f96193a5621be6f442e711f194
- Size of remote file:
- 335 MB
- SHA256:
- ecd7c8e0c83d1e259ebbc2cad843515d6976b5513fa146f2df413e62695b2750
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.