metadata

size_categories: n<1K
dataset_info:
  features:
    - name: text
      dtype: string
    - name: label
      dtype:
        class_label:
          names:
            '0': beauty-enhancement
            '1': other
            '2': relaxation
            '3': stress-relief
            '4': self-improvement
  splits:
    - name: train
      num_bytes: 2053
      num_examples: 10
  download_size: 3507
  dataset_size: 2053
configs:
  - config_name: default
    data_files:
      - split: train
        path: data/train-*
tags:
  - synthetic
  - distilabel
  - rlaif
  - datacraft

Dataset Card for my-distiset-1e19c746

This dataset has been created with distilabel.

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:

distilabel pipeline run --config "https://huggingface.co./datasets/R87/my-distiset-1e19c746/raw/main/pipeline.yaml"

or explore the configuration:

distilabel pipeline info --config "https://huggingface.co./datasets/R87/my-distiset-1e19c746/raw/main/pipeline.yaml"

Dataset structure

The examples have the following structure per configuration:

Configuration: default

{
    "label": 4,
    "text": "Maintaining a consistent self-care routine can have a profound impact on both physical and mental well-being, allowing individuals to better cope with stress and improve their overall quality of life."
}

This subset can be loaded as:

from datasets import load_dataset

ds = load_dataset("R87/my-distiset-1e19c746", "default")

Or simply as it follows, since there's only one configuration and is named default:

from datasets import load_dataset

ds = load_dataset("R87/my-distiset-1e19c746")