| --- |
| license: cc-by-nc-4.0 |
| library_name: pytorch |
| tags: |
| - audio |
| - deepfake-detection |
| - icml-2026 |
| --- |
| |
| # SONAR weights |
|
|
| Pretrained checkpoints for *SONAR: Spectral-Contrastive Audio Residuals |
| for Generalizable Deepfake Detection* (ICML 2026). |
|
|
| | File | ITW EER | Architecture | License | |
| |---|---:|---|---| |
| | `xlsr2_300m.pt` | — | XLSR-300M backbone (fairseq, derivative of [facebookresearch/fairseq](https://github.com/facebookresearch/fairseq/tree/main/examples/wav2vec/xlsr)). | CC-BY-NC-4.0 (upstream) | |
| | `baseline_xlsr_aasist.pth` | ~10.5% | Single XLSR + AASIST baseline (paper Table 1 row "XLSR+AASIST"). | CC-BY-NC-4.0 | |
| | `sonar_full_xlsr_aasist_eer6.pth` | **6.0%** | SONAR-Full: dual XLSR + RFE + cross-attention + AASIST + JS-alignment loss. Matches `guided_model.GuidedModel`. | CC-BY-NC-4.0 | |
| | `sonar_finetune_xlsr_mamba_eer5p5.pth` | **5.5%** | SONAR-Finetune: frozen XLSR-Mamba content branch + RFE/NFE + cross-attention + Conformer head + JS-alignment loss. | CC-BY-NC-4.0 | |
|
|
| Code: <https://github.com/idonithid/SONAR-Audio-DF-Detection> |
| Project page: <https://idonithid.github.io/SONAR-Audio-DF-Detection/> |
|
|
| ## Loading |
|
|
| ```python |
| from huggingface_hub import hf_hub_download |
| import torch |
| from argparse import Namespace |
| from sonar.guided_model import GuidedModel |
| |
| ckpt = hf_hub_download(repo_id="idonithid/SONAR-weights", |
| filename="sonar_full_xlsr_aasist_eer6.pth") |
| xlsr = hf_hub_download(repo_id="idonithid/SONAR-weights", |
| filename="xlsr2_300m.pt") |
| import os; os.environ["SONAR_XLSR_CKPT"] = xlsr |
| |
| model = GuidedModel(Namespace(algo=4, batch_size=1, device="cuda"), "cuda").cuda() |
| model.load_state_dict(torch.load(ckpt, map_location="cuda"), strict=False) |
| model.eval() |
| ``` |
|
|
| ## Citation |
|
|
| ```bibtex |
| @inproceedings{hidekel2026sonar, |
| title = {{SONAR}: Spectral-Contrastive Audio Residuals for Generalizable Deepfake Detection}, |
| author = {Hidekel, Ido Nitzan and Lifshitz, Gal and Cohen, Khen and Raviv, Dan}, |
| booktitle = {Proceedings of the 43rd International Conference on Machine Learning (ICML)}, |
| year = {2026} |
| } |
| ``` |
|
|
