Instructions to use Badd/SkinDiffusers with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Badd/SkinDiffusers with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Badd/SkinDiffusers", 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
- Xet hash:
- 251635c33346296ae87c2f244c0722fd70e9f0ee8c58db0934ee2f5d20c55227
- Size of remote file:
- 6.23 GB
- SHA256:
- f988ee752e4153f76c1224911a7247116675dd03da4c06f16272fc12a3772125
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.