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---
license: apache-2.0
tags: [braindecode, eeg, ieeg, mvpformer, seizure-detection]
library_name: braindecode
---

# MVPFormer-S backbone

Generatively pre-trained MVPFormer-S on the SWEC iEEG dataset.

```python
from braindecode.models import MVPFormer

model = MVPFormer.from_pretrained("braindecode/mvpformer-s-pretrained")
```

**The classification head is randomly initialised** — fine-tune it, or call `model.reset_head(n_outputs=...)`. Only the backbone is pre-trained.

## Licence and intended use

Weights © IBM Corp. 2024-2025, released under Apache-2.0 (`SPDX-License-Identifier: Apache-2.0`)
by <https://github.com/IBM/multi-variate-parallel-transformer>. Redistributed here unmodified in
substance; only the parameter names were remapped onto braindecode's `MVPFormer`.

The authors attach the following restriction, reproduced verbatim from the upstream README:

> This software may only be used for research. For other applications any liability is denied.
> In particular, the software must not be used for diagnostic purposes.

The paper's broader-impact statement adds: "both our model and our dataset are developed purely
for research, and may not be used for any other purpose, especially diagnostic."

## Citation

```bibtex
@article{carzaniga2025foundation,
  title={A foundation model with multi-variate parallel attention to generate neuronal activity},
  author={Carzaniga, Francesco and Hersche, Michael and Sebastian, Abu and Schindler, Kaspar and Rahimi, Abbas},
  journal={arXiv preprint arXiv:2506.20354},
  year={2025}
}
```