Instructions to use NO8D/FaceControl with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use NO8D/FaceControl with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("black-forest-labs/FLUX.2-klein-9B", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("NO8D/FaceControl") prompt = "-" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- 7ee8dc891eb6d105c94c5564fd3e79ad5d00c77120fde88790ec199b565f7530
- Size of remote file:
- 41.4 MB
- SHA256:
- 6463c30aa78951ce74620b4496d1ccecdf05778aa0a00faa448dbaa25a12fcc5
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