Instructions to use Muapi/fisting with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Muapi/fisting 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/fisting") 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:
- 145c660234ea214cf8a022c6e2b4a212797bffdc2a3029f0ab9f7e20474d2836
- Size of remote file:
- 1.2 MB
- SHA256:
- d933ed93fd2df96e07f67993704c191eff7446086cd02fc693de06014d2fcd05
路
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