--- library_name: braindecode license: bsd-3-clause tags: - CodeBrain - braindecode - model_hub_mixin - pytorch_model_hub_mixin datasets: - TUEG --- This model has been pushed to the Hub using the [PytorchModelHubMixin](https://huggingface.co/docs/huggingface_hub/package_reference/mixins#huggingface_hub.PyTorchModelHubMixin) integration: - Code: https://braindecode.org - Paper: [More Information Needed] - Docs: https://braindecode.org/stable/generated/braindecode.models.CodeBrain.html ## 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](https://nemar.org) (`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)](https://isip.piconepress.com/projects/nedc/html/tuh_eeg/) | pretraining | EEG | - stage 1 TFDual-Tokenizer (20 epochs) and stage 2 EEGSSM masked code prediction (10 epochs), both on TUEG; 19 ch, 200 Hz, 1,109,545 samples (~9,246 h); TUAB/TUEV not removed in the main model - `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:2506.09110 Sec. 3.1 (Datasets, Pre-Training); arXiv:2506.09110 Appendix (TUAB/TUEV results); braindecode/models/codebrain.py (W/bd) _remap docstring; HF commit braindecode/codebrain-pretrained 2026-04-03. ## Pretrained components Only the tokenizer/encoder weights are pretrained. The task classification head in this braindecode export is newly initialized; fine-tune it for your downstream task. ## Cite Braindecode If you use this braindecode port in scientific work, cite the software on Zenodo, [doi:10.5281/zenodo.17699192](https://doi.org/10.5281/zenodo.17699192), and the original model and datasets cited above. ```bibtex @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}, } ```