Instructions to use KevinHuang/OmniX with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use KevinHuang/OmniX with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("KevinHuang/OmniX", 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
Remove library name, update pipeline tag
#2
by nielsr HF Staff - opened
It looks like this model isn't compatible with Diffusers.
I am quite sure that it is compatible with diffusers; the proposed OmniXPipeline model directly inherits from diffusers' FluxPipeline.
Oh ok, will close this one.
nielsr changed pull request status to closed