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': kapha
          '1': vata
          '2': pitta-kapha
          '3': pitta
          '4': vata-kapha
          '5': vata-pitta
  splits:
  - name: train
    num_bytes: 53226
    num_examples: 93
  download_size: 26500
  dataset_size: 53226
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-80f9dbea

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/dark987/my-distiset-80f9dbea/raw/main/pipeline.yaml"
```

or explore the configuration:

```console
distilabel pipeline info --config "https://huggingface.co/datasets/dark987/my-distiset-80f9dbea/raw/main/pipeline.yaml"
```

## Dataset structure

The examples have the following structure per configuration:


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

```json
{
    "label": 1,
    "text": "This individual has a slender build, with a tendency to get cold easily and have dry skin, their hair is fine and brittle. They often experience digestive issues with a slow bowel movement, and exhibit anxiety and worry in response to stress. They prefer a calm and stable climate, tend to overthink before eating, and often wake up in the middle of the night. They exercise regularly but tend to overdo it, leading to exhaustion. They are a 35-year-old female."
}
```

This subset can be loaded as:

```python
from datasets import load_dataset

ds = load_dataset("dark987/my-distiset-80f9dbea", "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("dark987/my-distiset-80f9dbea")
```


</details>




