Datasetpublic

jeremycochoy/contrastive-training-small-bundles

small_mixed_v1 Pre-shuffled, pre-mixed training bundle for the Small tier (42.5M params) of the contrastive forecasting model family. Total rows: 27282687 Number of shards: 2736 Per-source row counts (source_id -> rows) 0 gift: 20250495 (74.2%) 1 wiki_hourly: 3715121 (13.6%) 2 wiki_daily: 1990244 (7.3%) 3 wiki_stl_residual: 530731 (1.9%) 4 wiki_stl_seasonal: 371512 (1.4%) 5 wiki_stl_trend: 159219 (0.6%) 6 synthetic: 265365 (1.0%) Schema… See the full description on the dataset page: https://huggingface.co/datasets/jeremycochoy/contrastive-training-small-bundles.

sourceHugging Faceupdated 5mo agoView on Hugging Face

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smallmixedv1

Pre-shuffled, pre-mixed training bundle for the Small tier (42.5M params) of the contrastive forecasting model family.

—Total rows: 27282687
—Number of shards: 2736

Per-source row counts (source_id -> rows)

—0 gift: 20250495 (74.2%)
—1 wiki_hourly: 3715121 (13.6%)
—2 wiki_daily: 1990244 (7.3%)
—3 wikistlresidual: 530731 (1.9%)
—4 wikistlseasonal: 371512 (1.4%)
—5 wikistltrend: 159219 (0.6%)
—6 synthetic: 265365 (1.0%)

Schema

Column	Type	Notes
		Fixed-length window
		0=gift, 1..5=wiki sub-sources, 6=synthetic
		Source-specific metadata

Shuffling and sampling

Globally shuffled via two-pass bucket shuffle (stage 3). Every output shard is a statistically uniform random sample of the entire input. Max mix-ratio delta between first and last shard: 0.009.

GIFT per-file sampling is byte-weighted. See the generating repo () for details.

NaN rate: 0.06% all-NaN, 0.22% partial-NaN. Consumers should forward-fill partial NaN and skip all-NaN rows.

Generated by (PRs #194-#202).