Instructions to use ckpt/SDHK with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use ckpt/SDHK with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("ckpt/SDHK", 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:
- 9fcbc7a87b3e25149c18b0cba3ad625323e49fdbffb4ed9b31994654d39ec451
- Size of remote file:
- 492 MB
- SHA256:
- 78196368b484307e1837ea5614f572d6991f986cda56165407ae574a9ac5fe8a
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