size_categories:n<1K format:parquet modality:text library:datasets library:pandas library:mlcroissant library:polars library:distilabel region:us synthetic distilabel rlaif
---
size_categories: n<1K
dataset_info:
- config_name: default
  features:
  - name: instruction
    dtype: string
  - name: targets
    dtype: string
  - name: language
    dtype: string
  - name: language_code
    dtype: string
  - name: annotation_type
    dtype: string
  - name: user_id
    dtype: string
  - name: zephyr-response
    dtype: string
  - name: generation_model
    dtype: string
  - name: generation
    dtype: string
  splits:
  - name: train
    num_bytes: 114839
    num_examples: 60
  download_size: 80401
  dataset_size: 114839
- config_name: text_generation
  features:
  - name: instruction
    dtype: string
  - name: targets
    dtype: string
  - name: language
    dtype: string
  - name: language_code
    dtype: string
  - name: annotation_type
    dtype: string
  - name: user_id
    dtype: string
  - name: zephyr-response
    dtype: string
  - name: generation_model
    dtype: string
  - name: generation
    dtype: string
  splits:
  - name: train
    num_bytes: 192711
    num_examples: 100
  download_size: 128979
  dataset_size: 192711
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
- config_name: text_generation
  data_files:
  - split: train
    path: text_generation/train-*
tags:
- synthetic
- distilabel
- rlaif
---

<p align="left">
  <a href="https://github.com/argilla-io/distilabel">
    <img src="https://raw.githubusercontent.com/argilla-io/distilabel/main/docs/assets/distilabel-badge-light.png" alt="Built with Distilabel" width="200" height="32"/>
  </a>
</p>

# Dataset Card for aya_dpo2

This dataset has been created with [distilabel](https://distilabel.argilla.io/).

## Dataset Summary

This dataset contains a `pipeline.yaml` which can be used to reproduce the pipeline that generated it in distilabel using the `distilabel` CLI:

```console
distilabel pipeline run --config "https://huggingface.co/datasets/davanstrien/aya_dpo2/raw/main/pipeline.yaml"
```

or explore the configuration:

```console
distilabel pipeline info --config "https://huggingface.co/datasets/davanstrien/aya_dpo2/raw/main/pipeline.yaml"
```

## Dataset structure

The examples have the following structure per configuration:


<details><summary> Configuration: default </summary><hr>

```json
{
    "annotation_type": "original-annotations",
    "generation": "Belgi\u00eb werd een onafhankelijke staat in het jaar 1830. De correcte antwoord is C. 1830.",
    "generation_model": "upstage/SOLAR-10.7B-Instruct-v1.0",
    "instruction": "Vraag: In welk jaar werd Belgi\u00eb een onafhankelijke staat? A. 1800 B. 1825 C. 1830 D. 1856",
    "language": "Dutch",
    "language_code": "nld",
    "targets": "Antwoord: C. 1830",
    "user_id": "ca908e583236b208e473e89dae5c7b7d3daf3662e2bbf6606f0702c718bb5c06",
    "zephyr-response": "Dit is de vraag: In welk jaar werd Belgi\u00eb een onafhankelijke staat?\n\nA. 1800\nB. 1825\nC. 1830\nD. 1856\n\nDit zijn de keuzes:\n\nA. 1800\nB. 1825\nC. 1830\nD. 1856\n\nHet correcte antwoord is C: 1830."
}
```

This subset can be loaded as:

```python
from datasets import load_dataset

ds = load_dataset("davanstrien/aya_dpo2", "default")
```

Or simply as it follows, since there's only one configuration and is named `default`: 

```python
from datasets import load_dataset

ds = load_dataset("davanstrien/aya_dpo2")
```


</details>
