Upload folder using huggingface_hub

README.md

@@ -0,0 +1,36 @@
+---
+tags:
+- transcriptomics
+- dimensionality-reduction
+- kpca
+- TRACERx
+license: mit
+---
+
+# KPCA Model - samples mode - 64D
+
+Pre-trained kpca model for transcriptomic data compression.
+
+## Details
+- **Mode**: samples-centric compression
+- **Dimensions**: 64
+- **Training data**: TRACERx lung cancer transcriptomics
+- **Created**: 2026-01-10T13:21:20.422879
+
+## Usage
+
+```python
+import joblib
+from huggingface_hub import snapshot_download
+
+# Download model
+local_dir = snapshot_download("jruffle/kpca_samples_64d")
+model = joblib.load(f"{local_dir}/model.joblib")
+
+# For classical models (PCA/UMAP):
+# model contains: 'pca', 'umap', 'robust_scaler', 'gene_order'
+
+# For TabPFN models (with UMAP reduction):
+# model contains: 'tabpfn_embedding', 'umap_final', 'raw_embeddings', 'input_scaler', etc.
+# Uses UMAP instead of PCA for non-linear dimension reduction of TabPFN embeddings
+```

metadata.json

@@ -0,0 +1,20 @@
+{
+  "model_type": "kpca",
+  "mode": "samples",
+  "dimensions": 64,
+  "created": "2026-01-10T13:21:20.423126",
+  "keys": [
+    "kpca_model",
+    "input_scaler",
+    "n_components",
+    "actual_components",
+    "kernel",
+    "gamma",
+    "method",
+    "mode",
+    "row_ids",
+    "feature_ids",
+    "robust_scaler",
+    "reference_embeddings"
+  ]
+}

model.joblib

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:2eff71ef47b45501eaa571df8cf7055a9a1f1c9cc7246271f686f05c190c6f69
+size 171398050