size_categories:n<1K format:parquet modality:text library:datasets library:pandas library:mlcroissant library:polars library:distilabel arxiv:2408.02442 region:us synthetic distilabel rlaif
---
size_categories: n<1K
dataset_info:
  features:
  - name: text
    dtype: string
  - name: step_labels
    sequence: string
  splits:
  - name: train
    num_bytes: 39353
    num_examples: 50
  download_size: 27723
  dataset_size: 39353
configs:
- config_name: default
  data_files:
  - split: train
    path: data/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 multi-step-v1

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/ashercn97/multi-step-v1/raw/main/pipeline.yaml"
```

or explore the configuration:

```console
distilabel pipeline info --config "https://huggingface.co/datasets/ashercn97/multi-step-v1/raw/main/pipeline.yaml"
```

## Dataset structure

The examples have the following structure per configuration:


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

```json
{
    "step_labels": [
        "logical",
        "logical",
        "illogical",
        "illogical",
        "logical",
        "illogical"
    ],
    "text": "The game\u2019s development beginning in 2010 shows a commitment to long-term project planning and resource allocation. Retaining elements from Valkyria Chronicles II indicates a desire to maintain a sense of continuity within the series. Making the game more forgiving for newcomers could be seen as a strategic choice aimed at broadening the player base. However, some die-hard fans may argue that this could dilute the core experience that attracted them in the first place. The return of key figures like Raita Honjou and Hitoshi Sakimoto might suggest a desire to preserve the identity of the game series, which adds both familiarity and potentially elevated expectations among fans. Having"
}
```

This subset can be loaded as:

```python
from datasets import load_dataset

ds = load_dataset("ashercn97/multi-step-v1", "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("ashercn97/multi-step-v1")
```


</details>





## References


```
@misc{2408.02442,
Author = {Zhi Rui Tam and Cheng-Kuang Wu and Yi-Lin Tsai and Chieh-Yen Lin and Hung-yi Lee and Yun-Nung Chen},
Title = {Let Me Speak Freely? A Study on the Impact of Format Restrictions on Performance of Large Language Models},
Year = {2024},
Eprint = {arXiv:2408.02442},
}
```


