---
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_108
  features:
  - name: packet_loss
    dtype: float64
  - name: cpu_pct
    dtype: float64
  - name: pressure
    dtype: float64
  - name: current
    dtype: float64
  - name: temperature
    dtype: float64
  - name: uptime_hours
    dtype: float64
  - name: error_rate
    dtype: float64
  - name: disk_iops
    dtype: float64
  - name: latency_ms
    dtype: float64
  - name: humidity
    dtype: float64
  - name: voltage
    dtype: float64
  - name: mem_pct
    dtype: float64
  - name: throughput_gbps
    dtype: float64
  - name: fan_rpm
    dtype: float64
  - name: vibration
    dtype: float64
  - name: iot_15
    dtype: float64
  - name: iot_16
    dtype: float64
  - name: iot_17
    dtype: float64
  - name: iot_18
    dtype: float64
  - name: iot_19
    dtype: float64
  - name: iot_20
    dtype: float64
  - name: iot_21
    dtype: float64
  - name: iot_22
    dtype: float64
  - name: iot_23
    dtype: float64
  - name: iot_24
    dtype: float64
  - name: iot_25
    dtype: float64
  - name: iot_26
    dtype: float64
  - name: iot_27
    dtype: float64
  - name: iot_28
    dtype: float64
  - name: iot_29
    dtype: float64
  - name: iot_30
    dtype: float64
  - name: iot_31
    dtype: float64
  - name: iot_32
    dtype: float64
  - name: iot_33
    dtype: float64
  - name: iot_34
    dtype: float64
  - name: iot_35
    dtype: float64
  - name: iot_36
    dtype: float64
  - name: iot_37
    dtype: float64
  - name: iot_38
    dtype: float64
  - name: iot_39
    dtype: float64
  - name: iot_40
    dtype: float64
  - name: iot_41
    dtype: float64
  - name: iot_42
    dtype: float64
  - name: iot_43
    dtype: float64
  - name: iot_44
    dtype: float64
  - name: iot_45
    dtype: float64
  - name: iot_46
    dtype: float64
  - name: iot_47
    dtype: float64
  - name: iot_48
    dtype: float64
  - name: iot_49
    dtype: float64
  - name: iot_50
    dtype: float64
  - name: iot_51
    dtype: float64
  - name: iot_52
    dtype: float64
  - name: iot_53
    dtype: float64
  - name: iot_54
    dtype: float64
  - name: iot_55
    dtype: float64
  - name: iot_56
    dtype: float64
  - name: iot_57
    dtype: float64
  - name: iot_58
    dtype: float64
  - name: iot_59
    dtype: float64
  - name: iot_60
    dtype: float64
  - name: target
    dtype: int64
  - name: _source_meta
    dtype: large_string
  - name: health_30
    dtype: float64
  - name: health_53
    dtype: float64
  - name: health_18
    dtype: float64
  - name: health_17
    dtype: float64
  - name: hr_29
    dtype: float64
  - name: health_15
    dtype: float64
  - name: fever
    dtype: float64
  - name: hr_24
    dtype: float64
  - name: health_55
    dtype: float64
  - name: health_21
    dtype: float64
  - name: heart_rate
    dtype: float64
  - name: velocity
    dtype: float64
  - name: health_50
    dtype: float64
  - name: blood_pressure
    dtype: float64
  - name: hr_39
    dtype: float64
  - name: hr_16
    dtype: float64
  - name: temperature_k
    dtype: float64
  - name: bonus_pct
    dtype: float64
  - name: health_46
    dtype: float64
  - name: hr_32
    dtype: float64
  - name: purity
    dtype: float64
  - name: health_24
    dtype: float64
  - name: health_25
    dtype: float64
  - name: reaction_time
    dtype: float64
  - name: smoking
    dtype: float64
  - name: mass
    dtype: float64
  - name: pressure_pa
    dtype: float64
  - name: health_23
    dtype: float64
  - name: hr_23
    dtype: float64
  - name: glucose
    dtype: float64
  - name: role_level
    dtype: float64
  - name: health_37
    dtype: float64
  - name: hr_26
    dtype: float64
  - name: health_44
    dtype: float64
  - name: health_36
    dtype: float64
  - name: white_cell_count
    dtype: float64
  - name: health_16
    dtype: float64
  - name: health_56
    dtype: float64
  - name: hr_30
    dtype: float64
  - name: health_43
    dtype: float64
  - name: health_57
    dtype: float64
  - name: health_20
    dtype: float64
  - name: hr_41
    dtype: float64
  - name: tenure_years
    dtype: float64
  - name: salary
    dtype: float64
  - name: health_51
    dtype: float64
  - name: health_40
    dtype: float64
  - name: health_42
    dtype: float64
  - name: health_58
    dtype: float64
  - name: health_29
    dtype: float64
  - name: absences
    dtype: float64
  - name: health_52
    dtype: float64
  - name: hr_17
    dtype: float64
  - name: creatinine
    dtype: float64
  - name: health_19
    dtype: float64
  - name: health_34
    dtype: float64
  - name: health_39
    dtype: float64
  - name: hr_36
    dtype: float64
  - name: bmi
    dtype: float64
  - name: family_history
    dtype: float64
  - name: health_31
    dtype: float64
  - name: satisfaction
    dtype: float64
  - name: promotions
    dtype: float64
  - name: volume
    dtype: float64
  - name: exercise_days
    dtype: float64
  - name: attrition
    dtype: float64
  - name: health_27
    dtype: float64
  - name: health_49
    dtype: float64
  - name: hr_40
    dtype: float64
  - name: training_hours
    dtype: float64
  - name: health_54
    dtype: float64
  - name: hr_42
    dtype: float64
  - name: health_45
    dtype: float64
  - name: hr_21
    dtype: float64
  - name: team_size
    dtype: float64
  - name: health_41
    dtype: float64
  - name: hr_35
    dtype: float64
  - name: department_id
    dtype: float64
  - name: hr_27
    dtype: float64
  - name: health_32
    dtype: float64
  - name: cholesterol
    dtype: float64
  - name: ph
    dtype: float64
  - name: wavelength
    dtype: float64
  - name: entropy
    dtype: float64
  - name: hr_15
    dtype: float64
  - name: hr_25
    dtype: float64
  - name: diagnosis
    dtype: float64
  - name: overtime_hours
    dtype: float64
  - name: hr_18
    dtype: float64
  - name: health_28
    dtype: float64
  - name: peer_rating
    dtype: float64
  - name: intensity
    dtype: float64
  - name: hr_34
    dtype: float64
  - name: hr_22
    dtype: float64
  - name: performance_score
    dtype: float64
  - name: hemoglobin
    dtype: float64
  - name: health_33
    dtype: float64
  - name: hr_31
    dtype: float64
  - name: remote_days
    dtype: float64
  - name: age
    dtype: float64
  - name: hr_20
    dtype: float64
  - name: health_22
    dtype: float64
  - name: health_35
    dtype: float64
  - name: hr_37
    dtype: float64
  - name: health_47
    dtype: float64
  - name: health_26
    dtype: float64
  - name: hr_28
    dtype: float64
  - name: hr_33
    dtype: float64
  - name: hr_38
    dtype: float64
  - name: health_48
    dtype: float64
  - name: health_59
    dtype: float64
  - name: alcohol_units
    dtype: float64
  - name: health_38
    dtype: float64
  - name: concentration
    dtype: float64
  - name: hr_19
    dtype: float64
  - name: acceleration
    dtype: float64
  - name: energy_kj
    dtype: float64
  splits:
  - name: train
    num_bytes: 22950277
    num_examples: 12500
  download_size: 3406385
  dataset_size: 22950277
configs:
- config_name: datagen_108
  data_files:
  - split: train
    path: datagen_108/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 | 1,706,000 |
| Real-data batches | 0 |
| Synthetic batches | 46 |
| Last updated | 2026-03-12 15:19 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 |
| datagen_099 | synthetic | TreePrior | synthetic:TreePrior | 6 | 14500 | success |
| datagen_100 | synthetic | SCM | synthetic:SCM | 12 | 62500 | success |
| datagen_101 | synthetic | GaussianMixture | synthetic:GaussianMixture | 13 | 65500 | success |
| datagen_102 | synthetic | Polynomial | synthetic:Polynomial | 13 | 53000 | success |
| datagen_103 | synthetic | Regression | synthetic:Regression | 15 | 56500 | success |
| datagen_104 | synthetic | TimeSeries | synthetic:TimeSeries | 11 | 16500 | success |
| datagen_105 | synthetic | MixedType_TreePrior | synthetic:MixedType_TreePrior | 3 | 7500 | success |
| datagen_106 | synthetic | MixedType_SCM | synthetic:MixedType_SCM | 14 | 71000 | 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.