---
size_categories: n<1K
task_categories:
- text-classification
dataset_info:
  features:
  - name: text
    dtype: string
  - name: label
    dtype:
      class_label:
        names:
          '0': concerning
          '1': unconcerning
          '2': unsure
  splits:
  - name: train
    num_bytes: 34797
    num_examples: 92
  download_size: 19669
  dataset_size: 34797
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 Data

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/valcarese/Data/raw/main/pipeline.yaml"
```

or explore the configuration:

```console
distilabel pipeline info --config "https://huggingface.co/datasets/valcarese/Data/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 living room is cluttered with dirty laundry and old newspapers. There are broken appliances and torn furniture scattered all over the floor. The air is stale and smells of mold. The residents seem disorganized and confused."
}
```

This subset can be loaded as:

```python
from datasets import load_dataset

ds = load_dataset("valcarese/Data", "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("valcarese/Data")
```


</details>