Instructions to use DankCloth/2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use DankCloth/2 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("DankCloth/2", dtype=torch.bfloat16, device_map="cuda") prompt = "a photo of owen wilson man" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- 10fabd8696280d0179f8e69f690561428c15443ea9829914b163d1f0bfbc3c4b
- Size of remote file:
- 9.6 MB
- SHA256:
- d56d809bd55c99ed9557d6c1a421c7bc34539da5b8f9a4a3ed5d40f1e39f7601
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