Update model card

README.md

@@ -1,3 +1,65 @@
----
-license: mit
----
+---
+license: mit
+tags:
+  - medical-imaging
+  - computational-pathology
+  - survival-analysis
+  - multimodal
+  - tcga
+datasets:
+  - TCGA
+library_name: pytorch
+---
+
+# ProtoPathway
+
+Pretrained checkpoints, preprocessed cohort data, and the curated pathway
+graph for **ProtoPathway**, an interpretable-by-design multimodal framework
+for cancer survival prediction.
+
+See the [code repository](https://github.com/AmayaGS/ProtoPathway) for usage,
+training, and evaluation instructions.
+
+## Layout
+
+```
+pathways/                              shared curated Reactome + Hallmark pathways
+cohorts/{cohort}/
+    gene_expression.csv                preprocessed expression matrix
+    bipartite_graph.pt                 cohort-specific gene-pathway graph
+    labels.csv                         survival times, events, and bins
+    data_splits.pkl                    5-fold CV splits (SurvPath-compatible)
+    checkpoints/best_fold_{0..4}.pt    trained model weights
+```
+
+## Cohorts
+
+Five TCGA cohorts: BRCA (N=714), BLCA (N=359), COADREAD (N=227),
+HNSC (N=392), STAD (N=318). Gene expression is the preprocessed
+SurvPath release. WSI patch features (UNI2-h) are not redistributed
+here and should be obtained from the
+[Mahmood Lab](https://huggingface.co/MahmoodLab/UNI2-h) directly.
+
+## Quick load
+
+```python
+from huggingface_hub import snapshot_download
+
+# Everything for one cohort plus the shared pathway file
+snapshot_download(
+    repo_id="AmayaGS/ProtoPathway",
+    local_dir="./assets",
+    allow_patterns=["cohorts/TCGA-BLCA/*", "pathways/*"],
+)
+```
+
+## Citation
+
+```bibtex
+@article{protopathway2026,
+  title   = {ProtoPathway: Interpretable Multimodal Cancer Survival Prediction
+             via Prototype-Pathway Cross-Modal Attention},
+  author  = {...},
+  year    = {2026}
+}
+```