---
dataset_info:
- config_name: nontask_con1
  features:
  - name: id
    dtype: string
  - name: prompt
    dtype: string
  - name: if_ground_truth
    dtype: string
  - name: key
    dtype: string
  - name: spec_key
    dtype: string
  - name: original_dataset
    dtype: string
  - name: cell
    dtype: string
  - name: cell_n_constraints
    dtype: int64
  - name: rank_random
    dtype: int64
  splits:
  - name: train
    num_bytes: 10471
    num_examples: 32
  download_size: 10036
  dataset_size: 10471
- config_name: nontask_con3
  features:
  - name: id
    dtype: string
  - name: prompt
    dtype: string
  - name: if_ground_truth
    dtype: string
  - name: key
    dtype: string
  - name: spec_key
    dtype: string
  - name: original_dataset
    dtype: string
  - name: cell
    dtype: string
  - name: cell_n_constraints
    dtype: int64
  - name: rank_random
    dtype: int64
  splits:
  - name: train
    num_bytes: 18909
    num_examples: 32
  download_size: 13461
  dataset_size: 18909
- config_name: task_con1
  features:
  - name: id
    dtype: string
  - name: prompt
    dtype: string
  - name: if_ground_truth
    dtype: string
  - name: key
    dtype: string
  - name: spec_key
    dtype: string
  - name: original_dataset
    dtype: string
  - name: cell
    dtype: string
  - name: cell_n_constraints
    dtype: int64
  - name: rank_random
    dtype: int64
  splits:
  - name: train
    num_bytes: 40229
    num_examples: 32
  download_size: 30347
  dataset_size: 40229
- config_name: task_con3
  features:
  - name: id
    dtype: string
  - name: prompt
    dtype: string
  - name: if_ground_truth
    dtype: string
  - name: key
    dtype: string
  - name: spec_key
    dtype: string
  - name: original_dataset
    dtype: string
  - name: cell
    dtype: string
  - name: cell_n_constraints
    dtype: int64
  - name: rank_random
    dtype: int64
  splits:
  - name: train
    num_bytes: 48667
    num_examples: 32
  download_size: 33820
  dataset_size: 48667
language:
- en
license: other
tags:
- rl
- alignment
- evaluation
size_categories:
- 1K<n<100K
configs:
- config_name: nontask_con1
  data_files:
  - split: train
    path: nontask_con1/train-*
- config_name: nontask_con3
  data_files:
  - split: train
    path: nontask_con3/train-*
- config_name: task_con1
  data_files:
  - split: train
    path: task_con1/train-*
- config_name: task_con3
  data_files:
  - split: train
    path: task_con3/train-*
---

# geodesic-research/vea-uplift-2x2

Auto-generated by [`dataset-builder`](https://github.com/GeodesicResearch/dataset-builder).
Each config below is a separate dataset produced from a versioned YAML build
config. Load with:

```python
from datasets import load_dataset

ds = load_dataset("geodesic-research/vea-uplift-2x2", "<config_name>", revision="<commit-sha>")
```

Pin `revision=` to the specific commit SHA you want; without it, you get the
current HEAD of the dataset repo, which may change when the builder re-pushes.

## Configs

| Config | Source | Transform | Splits |
|--------|--------|-----------|--------|
| `nontask_con1` | ? | `map_column → map_column → map_column → map_column → map_column → map_column → map_column → map_column → hook → project` | none |
| `nontask_con3` | ? | `map_column → map_column → map_column → map_column → map_column → map_column → map_column → map_column → hook → project` | none |
| `task_con1` | ? | `map_column → map_column → map_column → map_column → map_column → map_column → map_column → map_column → hook → project` | none |
| `task_con3` | ? | `map_column → map_column → map_column → map_column → map_column → map_column → map_column → map_column → hook → project` | none |

## Provenance

### `nontask_con1`

**Source:** `jsonl_file` (see `nontask_con1.yaml`).
**Transform:** `map_column → map_column → map_column → map_column → map_column → map_column → map_column → map_column → hook → project`

```bash
python -m dataset_builder configs/nontask_con1.yaml --push
```

### `nontask_con3`

**Source:** `jsonl_file` (see `nontask_con3.yaml`).
**Transform:** `map_column → map_column → map_column → map_column → map_column → map_column → map_column → map_column → hook → project`

```bash
python -m dataset_builder configs/nontask_con3.yaml --push
```

### `task_con1`

**Source:** `jsonl_file` (see `task_con1.yaml`).
**Transform:** `map_column → map_column → map_column → map_column → map_column → map_column → map_column → map_column → hook → project`

```bash
python -m dataset_builder configs/task_con1.yaml --push
```

### `task_con3`

**Source:** `jsonl_file` (see `task_con3.yaml`).
**Transform:** `map_column → map_column → map_column → map_column → map_column → map_column → map_column → map_column → hook → project`

```bash
python -m dataset_builder configs/task_con3.yaml --push
```

## Reproducibility

All splits use `split_hash()` (MD5-based, seeded) so rebuilding from the same
config against the same source data produces identical partitions. For an
LLM-generated dataset, a provider's `seed` parameter is best-effort; pin
consumer loads to a specific HF commit SHA to avoid drift when the builder
re-pushes.

---

*This card is auto-generated by `dataset_builder.cards`.*