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: labels
    sequence:
      class_label:
        names:
          '0': sports
          '1': entertainment
          '2': business
          '3': science
          '4': environment
          '5': politics
          '6': health
  splits:
  - name: train
    num_bytes: 10020
    num_examples: 20
  download_size: 9527
  dataset_size: 10020
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-be899639

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/yian2024/my-distiset-be899639/raw/main/pipeline.yaml"
```

or explore the configuration:

```console
distilabel pipeline info --config "https://huggingface.co/datasets/yian2024/my-distiset-be899639/raw/main/pipeline.yaml"
```

## Dataset structure

The examples have the following structure per configuration:


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

```json
{
    "labels": [
        6,
        4,
        3
    ],
    "text": "Recent studies suggest that the increasing presence of microplastics in aquatic ecosystems may have a profound impact on the global food chain, particularly in regions where fish and shellfish are a primary source of nutrition. The widespread adoption of single-use plastics and inadequate waste management infrastructure have exacerbated the problem, leading to the ingestion of microplastics by marine animals. This phenomenon has sparked concerns among scientists and policymakers, who are now advocating for more stringent regulations on plastic production and disposal."
}
```

This subset can be loaded as:

```python
from datasets import load_dataset

ds = load_dataset("yian2024/my-distiset-be899639", "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("yian2024/my-distiset-be899639")
```


</details>




