| --- |
| 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`). |
|
|
