Instructions to use wangjian21/N_AS14 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use wangjian21/N_AS14 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_AS14") prompt = "nude sexual erotic bather body art" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- 7d05a95fc02dc1b50264e5b3d4d5f8b10cb6fd12fe802fa90b12b88fd9df8fd1
- Size of remote file:
- 6.59 MB
- SHA256:
- 84222167f5b773cca86584d405bf7bd5ed585cc6153ac2ae6fd9d979c8a0d14a
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.