---
size_categories: n<1K
dataset_info:
  features:
  - name: text
    dtype: string
  - name: labels
    sequence:
      class_label:
        names:
          '0': sci-fi
          '1': crime
          '2': adventure
          '3': fantasy
          '4': mystery
          '5': historical-romance
          '6': thriller
          '7': horror
          '8': romance
  splits:
  - name: train
    num_bytes: 3455
    num_examples: 10
  download_size: 5026
  dataset_size: 3455
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
tags:
- synthetic
- distilabel
- rlaif
- datacraft
---

<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 my-distiset-1e19c746

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/IAOlivar/my-distiset-1e19c746/raw/main/pipeline.yaml"
```

or explore the configuration:

```console
distilabel pipeline info --config "https://huggingface.co/datasets/IAOlivar/my-distiset-1e19c746/raw/main/pipeline.yaml"
```

## Dataset structure

The examples have the following structure per configuration:


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

```json
{
    "labels": [
        0,
        2,
        3,
        4,
        5,
        6
    ],
    "text": "The novel \u0027The Red Tent\u0027 is a beautifully written, historical-romance that delves into the lives of the biblical matriarch Dinah, offering a fresh perspective on the ancient world, a rich tapestry of female relationships, and a testament to the power of love and resilience in the face of adversity."
}
```

This subset can be loaded as:

```python
from datasets import load_dataset

ds = load_dataset("IAOlivar/my-distiset-1e19c746", "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("IAOlivar/my-distiset-1e19c746")
```


</details>