Instructions to use hohs/SiTH_diffusion with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use hohs/SiTH_diffusion with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("hohs/SiTH_diffusion", 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
- Xet hash:
- fb72b1b56adeaafa9a14b6045850d5023e09f9a8632371f82307adce085772aa
- Size of remote file:
- 1.45 GB
- SHA256:
- 0465458edf271efe936b7bb74d45340c366526bb64f5a624e7840b788e1aa46a
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.