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: 74859
    num_examples: 50
  download_size: 27417
  dataset_size: 74859
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-v1-500

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-v1-500/raw/main/pipeline.yaml"
```

or explore the configuration:

```console
distilabel pipeline info --config "https://huggingface.co/datasets/ashercn97/multi-step-v1-500/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",
        "logical",
        "logical",
        "logical",
        "illogical",
        "illogical",
        "illogical",
        "illogical",
        "illogical",
        "illogical",
        "illogical",
        "logical",
        "logical",
        "illogical",
        "logical",
        "logical",
        "illogical",
        "illogical",
        "logical",
        "illogical",
        "illogical",
        "illogical",
        "logical",
        "illogical",
        "logical",
        "illogical",
        "logical",
        "logical",
        "logical",
        "logical",
        "illogical",
        "logical",
        "illogical",
        "illogical",
        "logical",
        "logical",
        "illogical",
        "illogical",
        "illogical",
        "logical",
        "illogical",
        "logical",
        "illogical",
        "illogical",
        "illogical",
        "illogical",
        "illogical",
        "illogical",
        "illogical",
        "illogical",
        "logical",
        "illogical",
        "logical",
        "illogical",
        "logical",
        "logical",
        "logical",
        "logical",
        "illogical",
        "logical",
        "logical",
        "logical",
        "illogical"
    ],
    "text": "Your husband enjoys the intense and competitive nature of playing PUBG, which is popular among many gamers. This could indicate his preference for action-packed activities and online interactions. On the other hand, your love for listening to country music suggests that you appreciate lyrical storytelling and perhaps a more laid-back experience. It\u0027s interesting how gaming and music can coexist in relationships, providing both partners with their own forms of entertainment. Maybe you could introduce him to some country songs that highlight themes of resilience and adventure, similar to the experiences in gaming. Or perhaps he could share his PUBG experience with you in a way that aligns with the storytelling of country music. It\u0027s also possible"
}
```

This subset can be loaded as:

```python
from datasets import load_dataset

ds = load_dataset("ashercn97/multi-step-v1-500", "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-v1-500")
```


</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},
}
```


