metadata

size_categories: n<1K
task_categories:
  - text-classification
dataset_info:
  features:
    - name: text
      dtype: string
    - name: label
      dtype:
        class_label:
          names:
            '0': customer-service
            '1': ticket-price
            '2': product-quality
            '3': movie-selection
            '4': website-usability
  splits:
    - name: train
      num_bytes: 2733
      num_examples: 20
  download_size: 3578
  dataset_size: 2733
configs:
  - config_name: default
    data_files:
      - split: train
        path: data/train-*
tags:
  - synthetic
  - distilabel
  - rlaif
  - datacraft

Dataset Card for my-distiset-757331e7

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/601FloridaMan/my-distiset-757331e7/raw/main/pipeline.yaml"

or explore the configuration:

distilabel pipeline info --config "https://huggingface.co/datasets/601FloridaMan/my-distiset-757331e7/raw/main/pipeline.yaml"

Dataset structure

The examples have the following structure per configuration:

Configuration: default

{
    "label": 0,
    "text": "The user interface of DavidMovieHouse is quite intuitive but the selection of independent films could be more diverse."
}

This subset can be loaded as:

from datasets import load_dataset

ds = load_dataset("601FloridaMan/my-distiset-757331e7", "default")

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

from datasets import load_dataset

ds = load_dataset("601FloridaMan/my-distiset-757331e7")