Instructions to use Open-TO/Diff with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Open-TO/Diff with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Open-TO/Diff", 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:
- 09415bfdbe82179a89de3fb3f41e5ae9107102894c0b808f2ba61841369cf61e
- Size of remote file:
- 2.69 GB
- SHA256:
- cba2bb28befdf477ed0b943359b68dac0ec5a9578d7be944788830325dc53033
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