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Datasets:
ninaxu
/
faker-example

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distilabel
rlaif
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metadata
size_categories: n<1K
dataset_info:
  features:
    - name: column_name
      dtype: string
    - name: id_faker_arguments
      struct:
        - name: args
          struct:
            - name: letters
              dtype: string
            - name: text
              dtype: string
        - name: type
          dtype: string
    - name: column_content
      sequence: string
  splits:
    - name: train
      num_bytes: 4583
      num_examples: 4
  download_size: 7535
  dataset_size: 4583
configs:
  - config_name: default
    data_files:
      - split: train
        path: data/train-*
tags:
  - synthetic
  - distilabel
  - rlaif

Built with Distilabel

Dataset Card for faker-example

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/ninaxu/faker-example/raw/main/pipeline.yaml"

or explore the configuration:

distilabel pipeline info --config "https://huggingface.co/datasets/ninaxu/faker-example/raw/main/pipeline.yaml"

Dataset structure

The examples have the following structure per configuration:

Configuration: default 
{
    "column_content": [
        "594564793936",
        "422645724655",
        "142688374180",
        "151546611521",
        "685542688520",
        "041197636946",
        "742485071901",
        "259581023351",
        "242310937846",
        "161331443479",
        "089946558053",
        "892937709085",
        "371747353204",
        "130825763690",
        "715314093651",
        "199735005780",
        "776005192229",
        "533330763559",
        "133642433775",
        "400474040702",
        "236402665456",
        "359951161260",
        "858505534111",
        "035009831008",
        "909566483105",
        "849472289056",
        "234702877781",
        "264888822024",
        "047437476067",
        "482031650266",
        "275058435264",
        "042763642003",
        "504739016897",
        "052402347800",
        "661215629471",
        "346545308924",
        "790927754992",
        "927973073123",
        "500126151170",
        "989947453568",
        "769940564398",
        "043814193121",
        "215740713849",
        "301021291360",
        "322580292726",
        "033918946671",
        "482122191043",
        "637850719148",
        "368826758961",
        "267609231778"
    ],
    "column_name": "uplift_loan_id",
    "id_faker_arguments": {
        "args": {
            "letters": null,
            "text": "############"
        },
        "type": "id"
    }
}

This subset can be loaded as:

from datasets import load_dataset

ds = load_dataset("ninaxu/faker-example", "default")

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

from datasets import load_dataset

ds = load_dataset("ninaxu/faker-example")