Instructions to use SidXXD/debug with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use SidXXD/debug with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("SidXXD/debug", dtype=torch.bfloat16, device_map="cuda") prompt = "photo of a <new1> person" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- 9c739e034bb4d9226a23b7deb8d1e31972137b35ce9365e2065df63972ccd94f
- Size of remote file:
- 656 kB
- SHA256:
- 113a918adc64d9b654b0b73d4f0e489efce55c33196ce35ea7e9bdd6733063d1
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.