Downloads · 30 days
26
3% of all-time downloads
cerc-aai/BFM-EEG-700m
BFM-EEG-700m is a machine learning model from cerc-aai. Use it for the machine learning task on the model card, and read the license before you ship it in a product.
General-Purpose Brain Foundation Models for Time-Series Neuroimaging Data
Downloads · 30 days
26
3% of all-time downloads
All-time downloads
1K
Public
Parameters
709M
5.7 GB on disk
Likes
3
Public
Click a slice to open those files.
.bin2.8 GB · 50%
From the Hugging Face model README
General-Purpose Brain Foundation Models for Time-Series Neuroimaging Data
[General-Purpose Brain Foundation Models for Time-Series Neuroimaging Data]
Visit our GitHub to Get Started with the Model.
Here is colab notebook for inference of the Moabb dataset.
The training data used was the NMT EEG dataset. NMT is an open-source, annotated dataset comprising healthy and pathological EEG recordings. It consists of 2,417 recordings from unique participants, providing multichannel EEG data along with labels indicating the participants' pathological state, classified as normal or abnormal. Each EEG channel is treated as an independent time series, which is further divided into two segments: a context window for conditioning and a prediction target window.
Hyperparameters are the same as those used in the Chronos paper.