Instructions to use wangjian21/KM_4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use wangjian21/KM_4 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_4") prompt = "Kelly McKernan's style" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- 1bd8f8303a2a55e6d8cb2a2ab49b7632d1d540913076dee311fbe93ad2fd2133
- Size of remote file:
- 6.59 MB
- SHA256:
- c912c428e32e843f8cfdbbea1f869634585b39a06c5a63f741a2dd2ad609a9d0
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