Instructions to use FoivosPar/Arc2Face with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use FoivosPar/Arc2Face 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("FoivosPar/Arc2Face", dtype=torch.bfloat16, device_map="cuda") prompt = "Turn this cat into a dog" 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] - Notebooks
- Google Colab
- Kaggle
Commit History
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Update model card for Arc2Face Expression Adapter extension and add pipeline tag
Verified signatureThis PR updates the model card to prominently feature the new "ID-Consistent, Precise Expression Generation with Blendshape-Guided Diffusion" extension, which is the model described in the primary paper for this repository. Changes include: - Updating the main title to reflect the new paper: "ID-Consistent, Precise Expression Generation with Blendshape-Guided Diffusion (Arc2Face Extension)". - Updating the primary paper link in the header to point to the Hugging Face paper page ([https://huggingface.co/papers/2510.04706](https://huggingface.co/papers/2510.04706)) and retaining the original Arc2Face paper link for context. - Adding the `pipeline_tag: image-to-image` to the metadata, which ensures the model can be found through the corresponding filter on the Hugging Face Hub. - Rewriting the introduction to focus on the extension, based on the provided abstract. - Adding a new, prominent section for the "Arc2Face + Expression Adapter" with its image and description from the G…d60a5a0 -
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