Mirror the SleepFM sleep stager in braindecode format

README.md

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+---
+license: cc-by-nc-4.0
+library_name: braindecode
+tags:
+  - eeg
+  - polysomnography
+  - sleep-staging
+  - foundation-model
+  - braindecode
+---
+
+# SleepFMStager — pretrained sleep stager
+
+Mirror of the official **SleepFM** sleep-staging model, re-hosted for stable loading from
+[Braindecode](https://github.com/braindecode/braindecode).
+
+SleepFM is a multimodal polysomnography (PSG) foundation model introduced in:
+
+> R. Thapa et al., *"A multimodal sleep foundation model for disease prediction,"*
+> **Nature Medicine** (2026). https://doi.org/10.1038/s41591-025-04133-4
+
+## Files
+
+| File | Description |
+|------|-------------|
+| `model.safetensors` | The full stager, with the parameter names of `braindecode.models.SleepFMStager` |
+| `config.json` | Architecture of the checkpoint, read by `from_pretrained()` |
+
+Upstream ships the stager in two pieces: the channel-agnostic tokenizer lives in the
+encoder checkpoint (`model_base/best.pt`) and the staging head in
+`model_sleep_staging/best.pth`. This file **merges both**, so a single call returns a
+model that is pretrained end to end, its five-class output layer included. The tensors are
+those of the upstream artifacts; only the keys were rewritten to the library's parameter
+names. Loading this file or the two upstream ones gives bit-identical outputs.
+
+The upstream artifacts themselves are kept, byte-for-byte, in
+[`braindecode/SleepFM`](https://huggingface.co/braindecode/SleepFM).
+
+## Usage
+
+```python
+from braindecode.models import SleepFMStager
+
+# Defaults to this repository.
+model = SleepFMStager.from_pretrained(n_chans=4, n_outputs=5, n_times=3840, sfreq=128)
+model.eval()
+```
+
+The output has shape `(batch, n_outputs, n_patches)`: one prediction per **5-second
+patch**, not per 30-second scoring epoch, so six predictions cover one scored epoch. For
+this checkpoint the five classes are Wake, N1, N2, N3 and REM. Input must be sampled at
+**128 Hz**. Pass `n_outputs` different from 5 to reinitialise the output layer for another
+label set.
+
+## License & attribution
+
+- **License: Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0).**
+- Copyright (c) 2025 Rahul Thapa.
+- Upstream source: https://github.com/zou-group/sleepfm-clinical
+
+These weights are **not** covered by Braindecode's BSD-3 license and inherit the
+upstream **noncommercial** terms. Re-hosted for reproducibility and stable
+availability only; attribution and the CC BY-NC 4.0 restriction are preserved.

config.json

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+{
+  "n_outputs": 5,
+  "n_chans": 4,
+  "chs_info": null,
+  "n_times": 3840,
+  "input_window_seconds": null,
+  "sfreq": 128.0,
+  "patch_size": 640,
+  "embed_dim": 128,
+  "staging_num_heads": 4,
+  "staging_num_layers": 1,
+  "staging_pooling_heads": 4,
+  "drop_prob": 0.3,
+  "max_seq_length": 8196,
+  "activation": "torch.nn.modules.activation.ELU"
+}

model.safetensors

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+size 9702172