Instructions to use wangjian21/N_AS12 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use wangjian21/N_AS12 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_AS12") prompt = "nude sexual erotic bather body art" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee

- Xet hash:
- 21ba623f8650d3e356232537c525532c159b235863e2914a2094e4938ab29eb2
- Size of remote file:
- 547 kB
- SHA256:
- 7ce621e223eb096f3ca616ec576b2d9871c87e24ecb6772a01da3dbee65e8047
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.