Instructions to use loyal-misc/swizz with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use loyal-misc/swizz with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("LyliaEngine/Pony_Diffusion_V6_XL", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("loyal-misc/swizz") prompt = "-" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- 4bfca62671dd08edaa12d976c4a900e316ad83f600ae20369e0e24def60894c5
- Size of remote file:
- 913 MB
- SHA256:
- f2dba5d8bb9851203d112475dbf26d5deacf91a83d4160d1d9d1af187431022b
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.