Instructions to use Alissonerdx/BFS-Best-Face-Swap-Video with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Alissonerdx/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-2.3,ByteDance/Bernini-R", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("Alissonerdx/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
It works
#4
by horsten - opened
But a 1GB LoRA to achieve this seems a bit excessive, you should look into DPO training.
Below 128 it doesn't work, I've already tried and the results are terrible, it doesn't capture what it needs. And you can be sure that when I say I've tried, I really mean it; I have thousands of attempts with different strategies.
Alissonerdx changed discussion status to closed