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:
- 72c73553613525c4dc38dd6edb4b9a28d6cec22e7240d46f22c4c36c7535859a
- Size of remote file:
- 3.44 kB
- SHA256:
- c61e977b0f31ce58a009bf837362602b9d137975e86c29d9dde525f11853189c
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