Instructions to use ilkerzgi/face-swap with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use ilkerzgi/face-swap with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline from diffusers.utils import load_image # 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("ilkerzgi/face-swap") prompt = "face_swap: take the face from Picture 1 and swap it onto the person in Picture 2. the result should show the exact face and features from Picture 1 on the body, pose, and scene from Picture 2, with natural skin tone blending and matching lighting." input_image = load_image("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/cat.png") image = pipe(image=input_image, prompt=prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- Xet hash:
- 59806d423134528f70003a1bae11eb13e739bd14b6d028812816dfd3aa10ddee
- Size of remote file:
- 127 MB
- SHA256:
- 40ad042e09c938cc587864b896690daf4f30abda86c24812d6a074aa041c25ec
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