Instructions to use wangjian21/N_AS10 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use wangjian21/N_AS10 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("stable-diffusion-v1-5/stable-diffusion-v1-5", torch_dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("wangjian21/N_AS10") prompt = "nude sexual erotic bather body art" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee

- Xet hash:
- 18ded953563dfd5bf18e495044da6bd9f7d5e79fe7b1592970a3f1494492b6fd
- Size of remote file:
- 482 kB
- SHA256:
- cd53227b3a7c9d4066133bb58c0c2195d75b1bb37ab99a0f889435c1e585329a
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.