metadata

size_categories: n<1K
task_categories:
  - text-classification
dataset_info:
  features:
    - name: text
      dtype: string
    - name: label
      dtype:
        class_label:
          names:
            '0': accept_recommendation
            '1': reject_recommendation
            '2': provide_reference
            '3': inquire
  splits:
    - name: train
      num_bytes: 19565
      num_examples: 100
  download_size: 9287
  dataset_size: 19565
configs:
  - config_name: default
    data_files:
      - split: train
        path: data/train-*
tags:
  - synthetic
  - distilabel
  - rlaif
  - datacraft

Dataset Card for dataset-200

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/omp1234/dataset-200/raw/main/pipeline.yaml"

or explore the configuration:

distilabel pipeline info --config "https://huggingface.co/datasets/omp1234/dataset-200/raw/main/pipeline.yaml"

Dataset structure

The examples have the following structure per configuration:

Configuration: default

{
    "label": 3,
    "text": "I am interested in understanding how UTMIST applies machine learning algorithms to personalize education for students with learning disabilities."
}

This subset can be loaded as:

from datasets import load_dataset

ds = load_dataset("omp1234/dataset-200", "default")

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

from datasets import load_dataset

ds = load_dataset("omp1234/dataset-200")