Instructions to use wangjian21/KM_12 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use wangjian21/KM_12 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_12") prompt = "Kelly McKernan's style" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- 3364b10f7c038d3d60983217439999677644178adc4be2f7c288d69d888f2c60
- Size of remote file:
- 6.59 MB
- SHA256:
- 34fa4d980d67aab5e221482d6ed55f3f98d968d4900f12bf29e9b1770c5ce6df
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.