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:
- 2b799c931d7a915e735620d0059bb69eed6976f12dc2a6efb2a5be89aa756eb6
- Size of remote file:
- 167 MB
- SHA256:
- 0cf7e0135a1bcb43b79ca8f441764fc48b8da8fc36aa8ace0c65c000dec73e28
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