metadata

size_categories: n<1K
task_categories:
  - text-classification
dataset_info:
  features:
    - name: text
      dtype: string
    - name: label
      dtype:
        class_label:
          names:
            '0': data-science-ai-ml
            '1': personal-development
            '2': energy-sector
            '3': finance
            '4': business
            '5': development
  splits:
    - name: train
      num_bytes: 3539
      num_examples: 12
  download_size: 5558
  dataset_size: 3539
configs:
  - config_name: default
    data_files:
      - split: train
        path: data/train-*
tags:
  - synthetic
  - distilabel
  - rlaif
  - datacraft

Dataset Card for my-distiset-ce202f9a

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/hjerpe/my-distiset-ce202f9a/raw/main/pipeline.yaml"

or explore the configuration:

distilabel pipeline info --config "https://huggingface.co./datasets/hjerpe/my-distiset-ce202f9a/raw/main/pipeline.yaml"

Dataset structure

The examples have the following structure per configuration:

Configuration: default

{
    "label": 1,
    "text": "As I reflect on the past year, I\u0027ve come to realize that my growth as an individual has been hindered by my tendency to procrastinate and lack of self-discipline. I\u0027ve been trying to establish a daily routine that includes time for meditation, reading, and exercise, but I often find myself getting distracted by social media and television. I\u0027m hoping to break free from these habits and develop a stronger sense of purpose and direction in life."
}

This subset can be loaded as:

from datasets import load_dataset

ds = load_dataset("hjerpe/my-distiset-ce202f9a", "default")

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

from datasets import load_dataset

ds = load_dataset("hjerpe/my-distiset-ce202f9a")