Instructions to use Muapi/buff with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Muapi/buff 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/buff") 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:
- befe106ef7fee158c4be6d39ef90b103814f6e8f6a2595bc45a772155b99c9c0
- Size of remote file:
- 1.26 MB
- SHA256:
- 1c8670660fa112b9e12b4396d80dbb7e6d1d096204a92b039776cb85b5b6c924
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