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int64
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The EEG Motor Movement/Imagery (MMI) Dataset preprocessed with DN3 to be used for downstream fine-tuning with BENDR.

The labels correspond to Task 4 (imagine opening and closing both fists or both feet) from experimental runs 4, 10 and 14.

Creating dataloaders

from datasets import load_dataset
from torch.utils.data import DataLoader

dataset = load_dataset("rasgaard/mmi-bendr-preprocessed")
dataset.set_format("torch")

train_loader = DataLoader(dataset["train"], batch_size=8)
val_loader = DataLoader(dataset["val"], batch_size=8)
test_loader = DataLoader(dataset["test"], batch_size=8)

batch = next(iter(train_loader))
batch["data"].shape, batch["label"].shape
>>> (torch.Size([8, 20, 1536]), torch.Size([8]))
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