This model has been pushed to the Hub using the PytorchModelHubMixin integration:

Training data

The data that shaped these weights. The ids are the datasets: field of this card, which braindecode reads into model.card_data.datasets when you call from_pretrained (MOABB class names for MOABB datasets, OpenNeuro / NEMAR accessions, Hub ids otherwise). nm/on ids are datasets on NEMAR (on = NEMAR's copy of the OpenNeuro dataset with the same number). Rows marked private: are data the authors did not release; they are not in datasets:.

datasets: id Dataset Stage Modality
TUEG Temple University Hospital EEG Corpus (TUH EEG) pretraining EEG
  • self-supervised (contrastive masked-sequence) on TUEG v1.1 and v1.2 (~1.5 TB EDF before preprocessing); no fine-tuning in this checkpoint (classification head randomly initialised)
  • TUEG (the TUH EEG Corpus) contains the recordings of its sub-corpora TUAB, TUEV, TUSZ, TUAR, TUSL and TUEP; an evaluation on one of those is not held out from these weights unless the authors removed it.
  • Sources: arXiv:2101.12037 p.5 (Sec. 3 / pre-training data); https://github.com/SPOClab-ca/BENDR/releases/tag/v0.1-alpha; HF commit braindecode/braindecode-bendr 2026-04-19 'Re-upload checkpoint in flat state_dict layout.'; size check.

Cite Braindecode

If you use this braindecode port in scientific work, cite the software on Zenodo, doi:10.5281/zenodo.17699192, and the original model and datasets cited above.

@software{braindecode,
  author = {Aristimunha, Bruno and
            Guetschel, Pierre and
            Wimpff, Martin and
            Gemein, Lukas and
            Rommel, Cedric and
            Banville, Hubert and
            Sliwowski, Maciej and
            Wilson, Daniel and
            Brandt, Simon and
            Gnassounou, Théo and
            Paillard, Joseph and
            {Junqueira Lopes}, Bruna and
            Sedlar, Sara and
            Moreau, Thomas and
            Chevallier, Sylvain and
            Gramfort, Alexandre and
            Schirrmeister, Robin Tibor},
  title = {Braindecode: toolbox for decoding raw electrophysiological brain data
           with deep learning models},
  url = {https://github.com/braindecode/braindecode},
  doi = {10.5281/zenodo.17699192},
  publisher = {Zenodo},
  license = {BSD-3-Clause},
}
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Paper for braindecode/braindecode-bendr