Instructions to use Worldsphere/OMI with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Worldsphere/OMI with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Worldsphere/OMI", torch_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:
- 1a9798b5ba93e264c8858e6870acdf1b452bd7d7a33bcefdb0613e81c48c8686
- Size of remote file:
- 3.18 GB
- SHA256:
- 74b7976b21605e48e94c15659c727c90e84884aa23dbdeba38d81f482dcab59e
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