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:
- 921c3b5895381081fd3df3aacc6b42f5a04be954ef5279eabe83120b7596661b
- Size of remote file:
- 604 kB
- SHA256:
- 142730c510737c9d6a3bf55bdd9e3da122b63d87e065b34430b6fba8a43a7908
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