README.md

metadata

license: cc-by-nc-4.0
language:
  - am
  - ha
  - nso
  - sw
  - yo
  - zu
size_categories:
  - 1K<n<10K
multilinguality:
  - multilingual
pretty_name: Uhura-TruthfulQA
language_details: am, ha, nso, sw, yo, zu
tags:
  - uhura
  - multilingual
  - multicultural
task_categories:
  - multiple-choice
task_ids:
  - multiple-choice-qa
configs:
  - config_name: am_generation
    data_files:
      - split: train
        path: am_gen_train.json
      - split: test
        path: am_gen_test.json
      - split: validation
        path: am_gen_val.json
  - config_name: am_multiple_choice
    data_files:
      - split: train
        path: am_mc1_train.json
      - split: test
        path: am_mc1_test.json
      - split: validation
        path: am_mc1_val.json
  - config_name: ha_multiple_choice
    data_files:
      - split: train
        path: ha_mc1_train.json
      - split: test
        path: ha_mc1_test.json
      - split: validation
        path: ha_mc1_val.json
  - config_name: sw_generation
    data_files:
      - split: train
        path: sw_gen_train.json
      - split: test
        path: sw_gen_test.json
      - split: validation
        path: sw_gen_val.json
  - config_name: sw_multiple_choice
    data_files:
      - split: train
        path: sw_mc1_train.json
      - split: test
        path: sw_mc1_test.json
      - split: validation
        path: sw_mc1_val.json
  - config_name: yo_multiple_choice
    data_files:
      - split: train
        path: yo_mc1_train.json
      - split: test
        path: yo_mc1_test.json
      - split: validation
        path: yo_mc1_val.json

Dataset Card for Uhura-TruthfulQA

Table of Contents

• Table of Contents
• Dataset Description
  • Dataset Summary
  • Languages
• Dataset Structure
  • Data Instances
  • Data Fields
  • Data Splits

Dataset Description

• Point of Contact:

Dataset Summary

Languages

There are 6 languages available:

• Amharic
• Hausa
• Northern Sotho (Sepedi)
• Swahili
• Yoruba
• Zulu

Dataset Structure

Data Instances

The examples look like this for English:

from datasets import load_dataset
data = load_dataset('ebayes/uhura-truthfulqa', 'yo_generation', split="train")