Instructions to use Muapi/incase-style with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Muapi/incase-style with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("cocktailpeanut/pony-diffusion-v6-xl", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("Muapi/incase-style") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee

- Xet hash:
- 2e2671943c33aec681745e665e0584e8378acab853ae1894886a1bbff26c05bb
- Size of remote file:
- 2.29 MB
- SHA256:
- 8c0bf88cd3e7f209058d4477bf4e1b348eef8ad1693f8d86b492685ab8fd9183
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