Instructions to use Muapi/chipmunking with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Muapi/chipmunking 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/chipmunking") 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:
- bfffd4feefd6f301482aa28a2f287d30e1f680ec47e1c676ce46e86675f7f461
- Size of remote file:
- 228 MB
- SHA256:
- 382768361987120c9fcf5834a1a8cc8d13916055fc903c414db5662f21f166ca
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