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license: cc-by-nc-4.0
library_name: braindecode
tags:
- eeg
- polysomnography
- sleep
- foundation-model
- braindecode
---
# SleepFM — pretrained checkpoints
Mirror of the official **SleepFM** checkpoints, 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 | Used by |
|------|-------------|---------|
| `model_base/best.pt` | Pretrained channel-agnostic PSG encoder (backbone) | `SleepFM.load_pretrained_backbone`, `SleepFMStager.load_pretrained_backbone` |
| `model_sleep_staging/best.pth` | Downstream sleep-staging head | `SleepFMStager.load_pretrained_staging_head` |
These are byte-for-byte copies of the upstream artifacts; only the hosting location
changed. The layout (`model_base/`, `model_sleep_staging/`) mirrors the upstream repo.
## Usage
```python
import torch
from braindecode.models import SleepFMStager
base = torch.hub.load_state_dict_from_url(
"https://huggingface.co/braindecode/SleepFM/resolve/main/model_base/best.pt",
map_location="cpu",
)
staging = torch.hub.load_state_dict_from_url(
"https://huggingface.co/braindecode/SleepFM/resolve/main/model_sleep_staging/best.pth",
map_location="cpu",
)
model = SleepFMStager(n_chans=4, n_outputs=5, n_times=3840, sfreq=128)
model.load_pretrained_backbone(base)
model.load_pretrained_staging_head(staging)
model.eval()
```
## 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.
|