size_categories:n<1K format:parquet modality:text library:datasets library:pandas library:mlcroissant library:polars library:distilabel region:us synthetic distilabel rlaif datacraft
---
size_categories: n<1K
dataset_info:
  features:
  - name: text
    dtype: string
  - name: label
    dtype:
      class_label:
        names:
          '0': cultural-shifts
          '1': social-changes
          '2': entertainment-industry
          '3': economic-challenges
          '4': political-events
          '5': historical-figures
  splits:
  - name: train
    num_bytes: 36270
    num_examples: 100
  download_size: 21173
  dataset_size: 36270
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/airjelly/my-distiset-1e19c746/raw/main/pipeline.yaml"
```

or explore the configuration:

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

## Dataset structure

The examples have the following structure per configuration:


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

```json
{
    "label": 0,
    "text": "The Harlem Renaissance, a cultural movement that celebrated African American art, literature, and music, reached its peak in the 1920s, with notable figures like Langston Hughes and Zora Neale Hurston gaining popularity. This movement marked a significant shift in the way Americans perceived and interacted with their black culture, promoting a sense of pride and identity among African Americans."
}
```

This subset can be loaded as:

```python
from datasets import load_dataset

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


</details>




