README.md

---
license: other
tags:
- eeg
- eeg-foundation-model
- neurotechx
- zuna
library_name: transformers
pipeline_tag: feature-extraction
---

# ZUNA — EEG Foundation Model (NeuroTechX HF-compatible build)

**ZUNA** is the [Zyphra](https://www.zyphra.com/) EEG foundation model — an
encoder–decoder architecture (encoder → latent embeddings; flow-matching diffusion
decoder), **382 M parameters**. This is a **self-contained, HuggingFace
`trust_remote_code` build** prepared by **NeuroTechX** so the model loads anywhere with
only `torch` + `transformers` + a few public pip deps — no private packages required.

Part of the [NeuroTechX EEG-FM Collection](https://huggingface.co/collections/NeuroTechX/eeg-foundation-models-6a443a79e9a158d702f2e8e1).

## Install
```bash
pip install torch transformers vector_quantize_pytorch einx einops
```

## Usage
```python
from transformers import AutoModel
model = AutoModel.from_pretrained("NeuroTechX/zuna", trust_remote_code=True).cuda().eval()

# encoder-only latents (the typical EEG-FM use):
latents = model.encode(encoder_input, seq_lens, ...)   # [B, L', encoder_output_dim]
```
Or, in the NeuroTechX stack: `make_hf_encoder("NeuroTechX/zuna")` (emeg-fm).

## What this build changes
A faithful mirror of the weights in
[`mhough/zuna-base`](https://huggingface.co/mhough/zuna-base), made **standalone**. The
original `modeling_zuna.py` imported a private `zuna` package, so it could not load via
`trust_remote_code` for anyone without that environment. Here the `EncoderDecoder`
architecture is **vendored** from the Zyphra source + Meta's
[`lingua`](https://github.com/facebookresearch/lingua) (MIT), imports rewritten to be
self-contained, and the train-only activation-probe stubbed to a no-op at inference.
**Weights are byte-identical** to the original.

## Attribution & license
- **Architecture & weights:** Zyphra (ZUNA).
- **Vendored framework:** Meta `lingua` (MIT).
- Licensing of the ZUNA weights should be confirmed with Zyphra; this build is offered
  in good faith for open EEG-FM research and reproducibility.