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1import joblib
2from huggingface_hub import snapshot_download
3
4# Download model
5local_dir = snapshot_download("jruffle/kpca_transcriptome_32d")
6model = joblib.load(f"{local_dir}/model.joblib")
7
8# For classical models (PCA/UMAP):
9# model contains: 'pca', 'umap', 'robust_scaler', 'gene_order'
10
11# For TabPFN models (with UMAP reduction):
12# model contains: 'tabpfn_embedding', 'umap_final', 'raw_embeddings', 'input_scaler', etc.
13# Uses UMAP instead of PCA for non-linear dimension reduction of TabPFN embeddings