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:
- afa3114f131c794f1216ec50105a15f71bd51be3bedcac67e2c8edbed75923c8
- Size of remote file:
- 145 kB
- SHA256:
- 8dcf305f42848383325f2ce23a02a38783201763c25e3ac9f315ae42995890af
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