task_categories:text-classification 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
task_categories:
- text-classification
dataset_info:
  features:
  - name: text
    dtype: string
  - name: label
    dtype:
      class_label:
        names:
          '0': positive
          '1': negative
          '2': neutral
  splits:
  - name: train
    num_bytes: 28535
    num_examples: 90
  download_size: 19057
  dataset_size: 28535
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-4c9252ac

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/evil2root/my-distiset-4c9252ac/raw/main/pipeline.yaml"
```

or explore the configuration:

```console
distilabel pipeline info --config "https://huggingface.co/datasets/evil2root/my-distiset-4c9252ac/raw/main/pipeline.yaml"
```

## Dataset structure

The examples have the following structure per configuration:


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

```json
{
    "label": 1,
    "text": "She has been feeling particularly melancholic lately, lost in the nostalgia of memories from her childhood, her eyes often welling up with tears when she thinks about her deceased grandmother, who would take her to the beach every summer. Her parents try to be supportive, but she\u0027s having trouble letting go of the past."
}
```

This subset can be loaded as:

```python
from datasets import load_dataset

ds = load_dataset("evil2root/my-distiset-4c9252ac", "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("evil2root/my-distiset-4c9252ac")
```


</details>




