metadata

size_categories: n<1K
dataset_info:
  features:
    - name: _id
      dtype: string
    - name: url
      dtype: string
    - name: title
      dtype: string
    - name: text
      dtype: string
    - name: score
      dtype: float64
    - name: views
      dtype: float64
    - name: model_name
      dtype: string
    - name: query
      dtype: string
  splits:
    - name: train
      num_bytes: 820541
      num_examples: 1500
  download_size: 534948
  dataset_size: 820541
configs:
  - config_name: default
    data_files:
      - split: train
        path: data/train-*
tags:
  - synthetic
  - distilabel
  - rlaif

Dataset Card for cohere-wikipedia-2023-11-no-queries

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/rasdani/cohere-wikipedia-2023-11-no-queries/raw/main/pipeline.yaml"

or explore the configuration:

distilabel pipeline info --config "https://huggingface.co/datasets/rasdani/cohere-wikipedia-2023-11-no-queries/raw/main/pipeline.yaml"

Dataset structure

The examples have the following structure per configuration:

Configuration: default

{
    "_id": "20231101.no_262035_4",
    "model_name": "gpt-4o",
    "query": "Hva er eksekutivfunksjoner i nevropsykologi?",
    "score": 1.0,
    "text": "Evne til \u00e5 strukturere, planlegge, igangsette og kontrollere sammensatte handlinger (eksekutivfunksjoner).",
    "title": "Nevropsykologi",
    "url": "https://no.wikipedia.org/wiki/Nevropsykologi",
    "views": 728.6967671316081
}

This subset can be loaded as:

from datasets import load_dataset

ds = load_dataset("rasdani/cohere-wikipedia-2023-11-no-queries", "default")

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

from datasets import load_dataset

ds = load_dataset("rasdani/cohere-wikipedia-2023-11-no-queries")