Instructions to use profpeng/wanhjbj with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use profpeng/wanhjbj with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("fill-in-base-model", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("profpeng/wanhjbj") prompt = "A sexy woman is giving a man a blowjob and a handjob. The man is out of frame. She is in front of the man. She is giving him a blowjob, while simultaneously giving a handjob. She is performing fellatio while stroking the shaft of his penis with one hand." image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- fa9f37ce94882e0ebd3ac8ca8239cf93ec1235c13feb36d7580dfb80bbc7eef8
- Size of remote file:
- 614 MB
- SHA256:
- 4371ed72fe9804257e69b56a37217bdab641b76a64208b07a75f5d716a25985d
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