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README.md

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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`).