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Card: list the training data (datasets:, base_model:) and add a Training data section

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Follow-up to braindecode PR #1493: `from_pretrained` reads `datasets:` into `model.card_data`. Ids: MOABB names, NEMAR nm/on ids, OpenNeuro ds ids; evidence per checkpoint.

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  1. README.md +22 -1
README.md CHANGED
@@ -6,9 +6,30 @@ tags:
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  - braindecode
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  - model_hub_mixin
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  - pytorch_model_hub_mixin
 
 
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  ---
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  This model has been pushed to the Hub using the [PytorchModelHubMixin](https://huggingface.co/docs/huggingface_hub/package_reference/mixins#huggingface_hub.PyTorchModelHubMixin) integration:
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  - Code: https://braindecode.org
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  - Paper: [More Information Needed]
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- - Docs: https://braindecode.org/stable/generated/braindecode.models.CodeBrain.html
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  - braindecode
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  - model_hub_mixin
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  - pytorch_model_hub_mixin
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+ datasets:
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+ - TUEG
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  ---
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  This model has been pushed to the Hub using the [PytorchModelHubMixin](https://huggingface.co/docs/huggingface_hub/package_reference/mixins#huggingface_hub.PyTorchModelHubMixin) integration:
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  - Code: https://braindecode.org
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  - Paper: [More Information Needed]
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+ - Docs: https://braindecode.org/stable/generated/braindecode.models.CodeBrain.html
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+
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+ <!-- braindecode:training-data -->
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+ ## Training data
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+
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+ The data that shaped these weights. The ids are the `datasets:` field of this card,
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+ which braindecode reads into `model.card_data.datasets` when you call
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+ `from_pretrained` (MOABB class names for MOABB datasets, OpenNeuro / NEMAR
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+ accessions, Hub ids otherwise). `nm`/`on` ids are datasets on [NEMAR](https://nemar.org)
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+ (`on` = NEMAR's copy of the OpenNeuro dataset with the same number). Rows marked
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+ `private:` are data the authors did not release; they are not in `datasets:`.
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+
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+ | `datasets:` id | Dataset | Stage | Modality |
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+ |---|---|---|---|
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+ | `TUEG` | [Temple University Hospital EEG Corpus (TUH EEG)](https://isip.piconepress.com/projects/nedc/html/tuh_eeg/) | pretraining | EEG |
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+
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+ - 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
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+ - `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.
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+ - 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.
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