---
size_categories: n<1K
task_categories:
- text-classification
dataset_info:
  features:
  - name: text
    dtype: string
  - name: label
    dtype:
      class_label:
        names:
          '0': aderente
          '1': não aderente
  splits:
  - name: train
    num_bytes: 4334
    num_examples: 13
  download_size: 5249
  dataset_size: 4334
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-cc40a8a8

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/luansouza4444/my-distiset-cc40a8a8/raw/main/pipeline.yaml"
```

or explore the configuration:

```console
distilabel pipeline info --config "https://huggingface.co/datasets/luansouza4444/my-distiset-cc40a8a8/raw/main/pipeline.yaml"
```

## Dataset structure

The examples have the following structure per configuration:


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

```json
{
    "label": 1,
    "text": "The notion that a society\u0027s overall well-being can be measured solely by its GDP has been widely criticized for neglecting the distribution of wealth and the human cost of economic growth, often referred to as the Easterlin paradox."
}
```

This subset can be loaded as:

```python
from datasets import load_dataset

ds = load_dataset("luansouza4444/my-distiset-cc40a8a8", "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("luansouza4444/my-distiset-cc40a8a8")
```


</details>