neuroencoder
EEG foundation model embeddings for Python.
pip install neuroencoder
import neuroencoder as ne
from neuroencoder import MRL
images = ne.preprocess(eeg, sfreq=256, channel_names=ch_names)
model = MRL.from_pretrained()
embeddings = model.predict(images, dim=192)
ne.explore(embeddings) # interactive Apple Embedding Atlas
ne.plot(embeddings) # static matplotlib UMAP
Model access
The MRL model is gated on HuggingFace. Request access, then authenticate once:
huggingface-cli login
or export HF_TOKEN=hf_... before running.
Documentation
Full docs at docs.neuroencoder.com.
- Introduction — what this is
- Quickstart — your first embedding
- Embeddings — the MRL model end-to-end
- Visualization — Apple Embedding Atlas
- Benchmarks — performance on 20 clinical EEG tasks
- API reference
Links
- Source: github.com/avocardio/neuroencoder
- Model weights: huggingface.co/Neuroencoder/epi-embedding
- Website: neuroencoder.com
1 maintainer
Metadata
1 maintainer
Release files for neuroencoder 1.0.1
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