Instructions to use Muapi/piledriver-pony with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Muapi/piledriver-pony 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/piledriver-pony") 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:
- 0dc7d278b5b241356cd87ce68217bf219531ba56ba681c213c28813b5d1e7b65
- Size of remote file:
- 3.75 MB
- SHA256:
- 23c4e174e85f9b371da1c4b9369554000243055c73305c5d1d10c2f38fe8af62
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