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:
- 47ec0f10af9af5dc74894fb5beaaa802539ac481f8584701492ae181a77d8db3
- Size of remote file:
- 41.4 MB
- SHA256:
- 484198af3c5dc0dc5107967b4778d7df277bea5309c270bdddb741f6ecdd7add
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