Instructions to use shivank21/Forget_Naked with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use shivank21/Forget_Naked with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("shivank21/Forget_Naked", 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
- Draw Things
- DiffusionBee
- Xet hash:
- bc03d881fe82fca7854d6891304ec628ff68ac52aa9b5f99a7ddf9dc1b525eea
- Size of remote file:
- 1.36 GB
- SHA256:
- baba2bebfd0ff73b70d28e174e86b068b7daff2341d7060dbaed739e6ee70031
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.