Upload README.md

README.md

@@ -0,0 +1,56 @@
+---
+license: mit
+library_name: pytorch
+tags:
+- hdtree
+- pytorch
+- mnist
+- single-cell
+- clustering
+---
+
+# HDTree ICML Checkpoints
+
+This repository hosts pretrained checkpoints for the public HDTree ICML release.
+
+Code: https://github.com/zangzelin/code_HDTree_icml
+
+## Files
+
+| File | Dataset | Configuration | Notes |
+|---|---|---|---|
+| `checkpoints/mnist/hdtree_mnist_best_epoch59_acc0.97570.pth` | MNIST | `configs/mnist.yaml` | Best MNIST checkpoint from the full run by checkpoint validation accuracy. |
+| `checkpoints/limb/hdtree_limb_i10_epoch199_acc0.53921.pth` | Limb | `configs/limb.yaml` default | Limb sweep i10/default checkpoint. |
+
+## Reported Metrics
+
+MNIST full run summary:
+
+| ACC | DP | LP | NMI |
+|---:|---:|---:|---:|
+| 0.97310 | 0.93262 | 0.97310 | 0.92999 |
+
+Limb i10 run summary (`batch_size=1000`, `K=10`, `exaggeration_lat=0.5`, `nu_lat=0.3`):
+
+| ACC | DP | LP | NMI |
+|---:|---:|---:|---:|
+| 0.52860 | 0.41029 | 0.58370 | 0.49042 |
+
+The included `logs/` files contain the original run outputs used to record these metrics.
+
+## Download
+
+```bash
+pip install huggingface_hub
+huggingface-cli download zangzelin/HDTree-ICML-checkpoints --local-dir .
+```
+
+Then use the public code repository's validation script, for example:
+
+```bash
+bash scripts/validate_checkpoint.sh checkpoints/limb/hdtree_limb_i10_epoch199_acc0.53921.pth
+```
+
+## Checksums
+
+See `SHA256SUMS`.