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language: en
tags:
- single-cell
- scRNA-seq
- representation-learning
- variational-autoencoder
- pytorch-lightning
---
# scTrilemma
Released checkpoint of **scTrilemma: Balancing Identity, Invariance, and Fidelity in
Single-Cell Representation Learning** (NeurIPS 2026).
- `final.ckpt` — PyTorch Lightning checkpoint (weights + model/data configuration, 223 MB),
SHA-256 `58981767d498c5d9c4087276bc2853cb6d5c338fc5048d84b3d8f8c9cacf5f76`.
- Trained for 25,000 steps on the 2025-01-30 CELLxGENE Census release (62.6 M cells, 478 datasets).
- Code, training recipe and evaluation: https://github.com/yunhak0/scTrilemma
## Usage
```bash
git clone https://github.com/yunhak0/scTrilemma && cd scTrilemma
pixi install --locked
bash scripts/download_checkpoint.sh
```
```python
from huggingface_hub import hf_hub_download
path = hf_hub_download("yunhak0/scTrilemma", "final.ckpt")
```
See the GitHub README for the inference API (`embed_adata`, `reconstruct_adata`).
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