Instructions to use udg/bra with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use udg/bra with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("udg/bra", 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 unet/diffusion_pytorch_model.bin from udg/bra: direct link, hf CLI and curl.
- Browser
- Download file 3.44 GB
-
https://huggingface.co/udg/bra/resolve/main/unet/diffusion_pytorch_model.bin
- Command line
-
hf download hf://udg/bra/unet/diffusion_pytorch_model.bin
-
curl -L -o diffusion_pytorch_model.bin https://huggingface.co/udg/bra/resolve/main/unet/diffusion_pytorch_model.bin
3.44 GB
- Xet hash:
- 325072a953760fe43847ea5c8764f44b5e12bc47f678ab40d95c4019e3b1d2f7
- Size of remote file:
- 3.44 GB
- SHA256:
- 3cb5721b3c9ee7c972dc822c91ce845fdaa70ec97d3460c7e7fae9be7b3b0487
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