--- license: other task_categories: - tabular-classification - tabular-regression language: - en tags: - tabular - synthetic - real-data - pretraining - tabpfn pretty_name: Tabula Pretraining Corpus dataset_info: config_name: datagen_100 features: - name: ph dtype: float64 - name: mass dtype: float64 - name: yield_pct dtype: float64 - name: intensity dtype: float64 - name: reaction_time dtype: float64 - name: volume dtype: float64 - name: wavelength dtype: float64 - name: concentration dtype: float64 - name: temperature_k dtype: float64 - name: purity dtype: float64 - name: entropy dtype: float64 - name: velocity dtype: float64 - name: acceleration dtype: float64 - name: pressure_pa dtype: float64 - name: energy_kj dtype: float64 - name: science_15 dtype: float64 - name: science_16 dtype: float64 - name: science_17 dtype: float64 - name: science_18 dtype: float64 - name: science_19 dtype: float64 - name: science_20 dtype: float64 - name: science_21 dtype: float64 - name: science_22 dtype: float64 - name: science_23 dtype: float64 - name: science_24 dtype: float64 - name: science_25 dtype: float64 - name: science_26 dtype: float64 - name: science_27 dtype: float64 - name: science_28 dtype: float64 - name: science_29 dtype: float64 - name: science_30 dtype: float64 - name: science_31 dtype: float64 - name: science_32 dtype: float64 - name: science_33 dtype: float64 - name: science_34 dtype: float64 - name: science_35 dtype: float64 - name: science_36 dtype: float64 - name: science_37 dtype: float64 - name: science_38 dtype: float64 - name: science_39 dtype: float64 - name: target dtype: int64 - name: _source_meta dtype: large_string - name: health_30 dtype: float64 - name: health_53 dtype: float64 - name: finance_29 dtype: float64 - name: finance_27 dtype: float64 - name: ecommerce_38 dtype: float64 - name: iot_40 dtype: float64 - name: science_40 dtype: float64 - name: interest_rate dtype: float64 - name: health_21 dtype: float64 - name: ecommerce_36 dtype: float64 - name: heart_rate dtype: float64 - name: finance_23 dtype: float64 - name: ecommerce_33 dtype: float64 - name: uptime_hours dtype: float64 - name: blood_pressure dtype: float64 - name: health_46 dtype: float64 - name: finance_28 dtype: float64 - name: health_24 dtype: float64 - name: finance_34 dtype: float64 - name: smoking dtype: float64 - name: finance_22 dtype: float64 - name: science_56 dtype: float64 - name: health_23 dtype: float64 - name: iot_44 dtype: float64 - name: glucose dtype: float64 - name: finance_26 dtype: float64 - name: fan_rpm dtype: float64 - name: iot_35 dtype: float64 - name: health_37 dtype: float64 - name: income dtype: float64 - name: ecommerce_34 dtype: float64 - name: health_44 dtype: float64 - name: science_48 dtype: float64 - name: shipping_days dtype: float64 - name: iot_30 dtype: float64 - name: health_36 dtype: float64 - name: finance_30 dtype: float64 - name: science_50 dtype: float64 - name: finance_18 dtype: float64 - name: cpu_pct dtype: float64 - name: iot_47 dtype: float64 - name: white_cell_count dtype: float64 - name: iot_45 dtype: float64 - name: ecommerce_16 dtype: float64 - name: health_16 dtype: float64 - name: health_43 dtype: float64 - name: iot_22 dtype: float64 - name: temperature dtype: float64 - name: science_53 dtype: float64 - name: iot_20 dtype: float64 - name: iot_36 dtype: float64 - name: health_20 dtype: float64 - name: science_52 dtype: float64 - name: health_51 dtype: float64 - name: health_40 dtype: float64 - name: iot_21 dtype: float64 - name: ecommerce_39 dtype: float64 - name: health_29 dtype: float64 - name: science_55 dtype: float64 - name: voltage dtype: float64 - name: science_54 dtype: float64 - name: error_rate dtype: float64 - name: iot_23 dtype: float64 - name: rating dtype: float64 - name: creatinine dtype: float64 - name: health_19 dtype: float64 - name: health_34 dtype: float64 - name: finance_32 dtype: float64 - name: family_history dtype: float64 - name: health_31 dtype: float64 - name: finance_15 dtype: float64 - name: exercise_days dtype: float64 - name: finance_37 dtype: float64 - name: finance_48 dtype: float64 - name: humidity dtype: float64 - name: science_46 dtype: float64 - name: conversion dtype: float64 - name: science_45 dtype: float64 - name: price dtype: float64 - name: health_45 dtype: float64 - name: iot_43 dtype: float64 - name: health_41 dtype: float64 - name: science_47 dtype: float64 - name: iot_41 dtype: float64 - name: finance_25 dtype: float64 - name: health_32 dtype: float64 - name: finance_19 dtype: float64 - name: cholesterol dtype: float64 - name: science_42 dtype: float64 - name: health_28 dtype: float64 - name: churn dtype: float64 - name: finance_16 dtype: float64 - name: hemoglobin dtype: float64 - name: assets dtype: float64 - name: discount dtype: float64 - name: health_22 dtype: float64 - name: iot_33 dtype: float64 - name: revenue dtype: float64 - name: health_35 dtype: float64 - name: finance_43 dtype: float64 - name: finance_31 dtype: float64 - name: health_26 dtype: float64 - name: iot_48 dtype: float64 - name: finance_24 dtype: float64 - name: balance dtype: float64 - name: health_48 dtype: float64 - name: finance_41 dtype: float64 - name: finance_40 dtype: float64 - name: iot_16 dtype: float64 - name: finance_46 dtype: float64 - name: iot_26 dtype: float64 - name: ecommerce_40 dtype: float64 - name: finance_51 dtype: float64 - name: ecommerce_20 dtype: float64 - name: pressure dtype: float64 - name: health_18 dtype: float64 - name: iot_37 dtype: float64 - name: iot_32 dtype: float64 - name: health_17 dtype: float64 - name: ecommerce_25 dtype: float64 - name: margin dtype: float64 - name: health_15 dtype: float64 - name: fever dtype: float64 - name: science_43 dtype: float64 - name: ecommerce_19 dtype: float64 - name: ecommerce_41 dtype: float64 - name: science_57 dtype: float64 - name: category dtype: float64 - name: vibration dtype: float64 - name: health_50 dtype: float64 - name: science_58 dtype: float64 - name: iot_49 dtype: float64 - name: finance_36 dtype: float64 - name: ecommerce_23 dtype: float64 - name: health_25 dtype: float64 - name: reviews dtype: float64 - name: refund dtype: float64 - name: finance_44 dtype: float64 - name: iot_29 dtype: float64 - name: finance_50 dtype: float64 - name: disk_iops dtype: float64 - name: finance_39 dtype: float64 - name: science_44 dtype: float64 - name: science_51 dtype: float64 - name: ecommerce_18 dtype: float64 - name: latency_ms dtype: float64 - name: ecommerce_28 dtype: float64 - name: ecommerce_37 dtype: float64 - name: iot_46 dtype: float64 - name: cart_size dtype: float64 - name: iot_27 dtype: float64 - name: health_42 dtype: float64 - name: finance_49 dtype: float64 - name: health_52 dtype: float64 - name: ecommerce_21 dtype: float64 - name: ecommerce_15 dtype: float64 - name: ecommerce_31 dtype: float64 - name: bmi dtype: float64 - name: finance_42 dtype: float64 - name: science_41 dtype: float64 - name: clicks dtype: float64 - name: mem_pct dtype: float64 - name: expenses dtype: float64 - name: default dtype: float64 - name: science_49 dtype: float64 - name: finance_38 dtype: float64 - name: ecommerce_29 dtype: float64 - name: ecommerce_17 dtype: float64 - name: ecommerce_35 dtype: float64 - name: finance_35 dtype: float64 - name: quantity dtype: float64 - name: health_27 dtype: float64 - name: health_49 dtype: float64 - name: employment_years dtype: float64 - name: finance_33 dtype: float64 - name: finance_45 dtype: float64 - name: ecommerce_26 dtype: float64 - name: ecommerce_24 dtype: float64 - name: current dtype: float64 - name: credit_score dtype: float64 - name: iot_42 dtype: float64 - name: iot_19 dtype: float64 - name: finance_21 dtype: float64 - name: ecommerce_27 dtype: float64 - name: finance_17 dtype: float64 - name: iot_25 dtype: float64 - name: iot_31 dtype: float64 - name: liabilities dtype: float64 - name: finance_20 dtype: float64 - name: packet_loss dtype: float64 - name: iot_28 dtype: float64 - name: iot_18 dtype: float64 - name: diagnosis dtype: float64 - name: session_minutes dtype: float64 - name: iot_34 dtype: float64 - name: iot_39 dtype: float64 - name: health_33 dtype: float64 - name: tax_rate dtype: float64 - name: iot_15 dtype: float64 - name: age dtype: float64 - name: iot_24 dtype: float64 - name: finance_47 dtype: float64 - name: loan_amount dtype: float64 - name: health_47 dtype: float64 - name: throughput_gbps dtype: float64 - name: return_rate dtype: float64 - name: debt_ratio dtype: float64 - name: iot_38 dtype: float64 - name: iot_17 dtype: float64 - name: alcohol_units dtype: float64 - name: health_38 dtype: float64 - name: ecommerce_30 dtype: float64 - name: ecommerce_32 dtype: float64 - name: ecommerce_22 dtype: float64 - name: health_39 dtype: float64 splits: - name: train num_bytes: 153391628 num_examples: 62500 download_size: 17295303 dataset_size: 153391628 configs: - config_name: datagen_100 data_files: - split: train path: datagen_100/train-* --- # Tabula Pretraining Corpus A continuously growing tabular pretraining corpus for the Tabula foundation model (tabPFN-style in-context learning). Built by an autonomous agent that alternates between harvesting permissively-licensed real datasets and generating high-quality synthetic ones. ## Stats (auto-updated) | Metric | Value | |--------|-------| | Total rows | 1,359,000 | | Real-data batches | 0 | | Synthetic batches | 38 | | Last updated | 2026-03-12 15:15 UTC | ## Schema Every row has feature columns plus `_source_meta` (JSON string): - `batch_id`, `source_type`, `source_id`, `domain`, `task_type`, `license`, `citation_key` ## Sources & Citations | batch_id | source_type | method | source_id | n_datasets | total_rows | status | |----------|-------------|--------|-----------|------------|------------|--------| | datagen_001 | synthetic | TreePrior | synthetic:TreePrior | 4 | 3500 | success | | datagen_002 | synthetic | TreePrior | synthetic:TreePrior | 6 | 17000 | success | | datagen_003 | synthetic | SCM | synthetic:SCM | 14 | 47000 | success | | datagen_004 | synthetic | TreePrior | synthetic:TreePrior | 5 | 17000 | success | | datagen_005 | synthetic | SCM | synthetic:SCM | 11 | 33000 | success | | datagen_003 | synthetic | SCM | synthetic:SCM | 12 | 35500 | success | | datagen_006 | synthetic | TreePrior | synthetic:TreePrior | 7 | 15500 | success | | datagen_006 | synthetic | TreePrior | synthetic:TreePrior | 7 | 28000 | success | | datagen_007 | synthetic | SCM | synthetic:SCM | 12 | 62500 | success | | datagen_008 | synthetic | TreePrior | synthetic:TreePrior | 5 | 17500 | success | | datagen_009 | synthetic | TreePrior | synthetic:TreePrior | 5 | 8500 | success | | datagen_009 | synthetic | SCM | synthetic:SCM | 10 | 32000 | success | | datagen_010 | synthetic | TreePrior | synthetic:TreePrior | 8 | 15500 | success | | datagen_011 | synthetic | SCM | synthetic:SCM | 13 | 56500 | success | | datagen_012 | synthetic | GaussianMixture | synthetic:GaussianMixture | 10 | 33500 | success | | datagen_013 | synthetic | Polynomial | synthetic:Polynomial | 14 | 39000 | success | | datagen_014 | synthetic | Regression | synthetic:Regression | 13 | 61500 | success | | datagen_078 | synthetic | MixedType_TreePrior | synthetic:MixedType_TreePrior | 5 | 6500 | success | | datagen_079 | synthetic | MixedType_SCM | synthetic:MixedType_SCM | 12 | 55000 | success | | datagen_080 | synthetic | MixedType_GaussianMixture | synthetic:MixedType_GaussianMixture | 11 | 47000 | success | | datagen_081 | synthetic | TreePrior | synthetic:TreePrior | 6 | 23500 | success | | datagen_082 | synthetic | SCM | synthetic:SCM | 15 | 46000 | success | | datagen_083 | synthetic | GaussianMixture | synthetic:GaussianMixture | 10 | 41000 | success | | datagen_084 | synthetic | Polynomial | synthetic:Polynomial | 15 | 95500 | success | | datagen_085 | synthetic | Regression | synthetic:Regression | 15 | 57500 | success | | datagen_086 | synthetic | TimeSeries | synthetic:TimeSeries | 12 | 19500 | success | | datagen_087 | synthetic | MixedType_TreePrior | synthetic:MixedType_TreePrior | 4 | 4000 | success | | datagen_088 | synthetic | MixedType_SCM | synthetic:MixedType_SCM | 13 | 46500 | success | | datagen_089 | synthetic | MixedType_GaussianMixture | synthetic:MixedType_GaussianMixture | 12 | 38000 | success | | datagen_090 | synthetic | TreePrior | synthetic:TreePrior | 4 | 31000 | success | | datagen_091 | synthetic | SCM | synthetic:SCM | 15 | 63000 | success | | datagen_092 | synthetic | GaussianMixture | synthetic:GaussianMixture | 8 | 34000 | success | | datagen_093 | synthetic | Polynomial | synthetic:Polynomial | 10 | 23000 | success | | datagen_094 | synthetic | Regression | synthetic:Regression | 14 | 74000 | success | | datagen_095 | synthetic | TimeSeries | synthetic:TimeSeries | 14 | 19500 | success | | datagen_096 | synthetic | MixedType_TreePrior | synthetic:MixedType_TreePrior | 8 | 25000 | success | | datagen_097 | synthetic | MixedType_SCM | synthetic:MixedType_SCM | 14 | 43500 | success | | datagen_098 | synthetic | MixedType_GaussianMixture | synthetic:MixedType_GaussianMixture | 12 | 43000 | success | ## Key Citations ```bibtex @inproceedings{hollmann2023tabpfn, title = {TabPFN: A Transformer That Solves Small Tabular Classification Problems in a Second}, author = {Hollmann, Noah and M{\"u}ller, Samuel and Eggensperger, Katharina and Hutter, Frank}, booktitle = {ICLR}, year = {2023} } @article{vanschoren2014openml, title = {OpenML: Networked Science in Machine Learning}, author = {Vanschoren, Joaquin and van Rijn, Jan N. and Bischl, Bernd and Torgo, Luis}, journal = {ACM SIGKDD Explorations}, year = {2014} } @article{scholkopf2021causal, title = {Toward Causal Representation Learning}, author = {Sch{\"o}lkopf, Bernhard and others}, journal = {Proceedings of the IEEE}, year = {2021} } ``` ## License Individual rows carry their own `license` field inside `_source_meta`. Synthetic rows are Apache 2.0. Real rows carry the original source license.