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:
- 3a3e15670bd48e3ee75c148f3624f0e50ffd41354d3f0deb432a64c08a007a89
- Size of remote file:
- 229 MB
- SHA256:
- b4b3dd26e3b3687491c2d5ea8360eef6f9f61e3f1602b2250678ca9ec9fbddd3
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