Instructions to use Yashumgr/BFS-Best-Face-Swap-Video with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Yashumgr/BFS-Best-Face-Swap-Video with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline from diffusers.utils import load_image, export_to_video # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Lightricks/LTX-2", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("Yashumgr/BFS-Best-Face-Swap-Video") prompt = "A man with short gray hair plays a red electric guitar." input_image = load_image("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/guitar-man.png") image = pipe(image=input_image, prompt=prompt).frames[0] export_to_video(output, "output.mp4") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- Xet hash:
- 9a0d5f0dd97a9e8bc9db6a2479fa3e8c755bfe91a379e9a36800dffaaec95357
- Size of remote file:
- 5.12 kB
- SHA256:
- 6427e10f9a4d9141c728ebef8e9c0908700bd94726be53effc85ecb99a78423b
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