Instructions to use KamCastle/aardvark with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use KamCastle/aardvark with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("KamCastle/aardvark", torch_dtype=torch.bfloat16, device_map="cuda") 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:
- dce098aa5d68c5e8e11e2bc47e84356ef2a0f067d27ff52c31a260ed7b00373b
- Size of remote file:
- 335 MB
- SHA256:
- 7cc254a95ac0a5902862ec2002a39bd673b0091484ac47dc50bad9d5d28ff87a
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