pretty_name: GenBench prepared benchmark datasets
license: other
GenBench prepared datasets
This repository contains the exact prepared arrays used by the canonical GenBench training and evaluation runs. It intentionally excludes redundant source archives: every benchmark's Python preparation module records and verifies the original upstream source, while these files are sufficient to train and evaluate the published baselines directly. DeepSTARR's small official activity-predictor weights are included because they are part of its evaluation protocol.
| Directory | Generative object | Prepared contents |
|---|---|---|
QM9 |
Molecular geometries | Packed characterized molecules and TD-jumps split rows |
MiniBooNE |
Particle events | Literature split and normalization |
NavierStokes |
Vorticity fields | Fourier-downsampled train/validation/test arrays |
JetNet30 |
Particle clouds | Five-class train/validation/test arrays |
DeepSTARR |
Enhancer sequences | Splits, activities, metadata, and official predictor weights |
GuacaMol |
Drug-like molecules | Official non-overlapping ChEMBL splits as canonical-SMILES tokens and exact lengths |
SpeechCommands |
One-second spoken-word waveforms | Official speaker-disjoint train/validation/test arrays and labels |
The analytic spiral and checkerboard benchmarks have no stored dataset; their target distributions are generated exactly by the GenBench Python package.
manifest.json is authoritative. It records the byte size and SHA-256 of every
required file. Original licenses and redistribution terms differ by dataset;
consult each dataset's metadata and upstream source before reuse. CIFAR-10 and
MNIST are deliberately absent because their upstream distributions do not
provide an affirmative general redistribution grant.