Instructions to use wangjian21/KM_500e with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use wangjian21/KM_500e 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_500e") prompt = "Kelly McKernan's style" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- 317003155ad47d9a4c334e89708f993b6c3782b409e13da3f4b3d8518238e1f5
- Size of remote file:
- 6.59 MB
- SHA256:
- 2f116e668d5b90558542f809cc9569ff3af472ebfc12bc1010f2dda35d29da61
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