GoyalLab/ExPert-paper-models

ExPert paper checkpoints

The additional checkpoints behind the ExPert paper's benchmark and ablation figures. The production model that the paper's application figures use, and that you should use for your own data, is GoyalLab/ExPert.

Code and the scripts that use these checkpoints: https://github.com/GoyalLab/ExPert (paper/)

folder	what	used in
fold0 … fold11	the 12 cross-validation models: each holds out one context (cell line / donor / condition) from training	benchmark and out-of-distribution figures
EFFGATE3	the ablation arm with the gated prior pull	prior-pull ablation figures
banks/v0.1.0_fullbank_oldfill.npz	v0.1.0 prototypes with the earlier fill for genes never perturbed in training (trained rows identical to the model's)	ALD and PMD readouts

Each checkpoint folder holds model.pt and gene_embeddings.npz and loads like the production model:

from huggingface_hub import snapshot_download
from expert import ExPert

path = snapshot_download("GoyalLab/ExPert-paper-models", revision="v0.1.0", allow_patterns="fold4/*")
model = ExPert.load(f"{path}/fold4")

The bank is a NumPy archive: P (perturbations × latent dims), labels, trained.

Citation

Preprint reference to be added.