Instructions to use wangjian21/KM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use wangjian21/KM 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/KM") prompt = "Kelly McKernan's style" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee

- Xet hash:
- 92bda0fe9681bc91fcc86194716de9f7e03dcad409151921fa27451f4fcce5f2
- Size of remote file:
- 626 kB
- SHA256:
- 047d35458f7524b3e6871737d63648c73300faea9e4e31d19d0524084f53d780
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.