Instructions to use ekato/MK with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use ekato/MK with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("stabilityai/stable-diffusion-3.5-large", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("ekato/MK") prompt = "-" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- 2a2880bf3d53b6e46eb34dfddf1b9797fca96156baff47101fcb4762375e5582
- Size of remote file:
- 69.9 MB
- SHA256:
- f3c48b655369b774b0048f5da3b3ac1a7a58acbac512ac2cd95a5e67e34b72f4
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