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:
- 672a18b6b1680ce5f493698b102e4cc1883379d2acd5554d85f605cbee74ba8c
- Size of remote file:
- 619 kB
- SHA256:
- 5df9007f47ec6a61b3ca855b302149f9d15583e3514ae06cee674af22eff8e99
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