Instructions to use yliuhz/FaceEditXL-ControlNet with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use yliuhz/FaceEditXL-ControlNet with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("yliuhz/FaceEditXL-ControlNet", 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:
- 512db40273ca89de14da235fbd036244b31eb1e3b21de20edea40d05221bdf07
- Size of remote file:
- 5 GB
- SHA256:
- 62d4bfed0c67675eef2413d6f17561f4f3937bffd6efa7cc3d90cee4a1b287da
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