---
dataset_info:
  features:
  - name: id
    dtype: string
  - name: context
    dtype: string
  - name: question
    dtype: string
  - name: answers
    struct:
    - name: answer_start
      list: int64
    - name: text
      list: string
  - name: lang
    dtype: string
  splits:
  - name: train
    num_bytes: 17768236.09346378
    num_examples: 11529
  - name: validation
    num_bytes: 2220836.864487927
    num_examples: 1441
  - name: test
    num_bytes: 2222378.042048293
    num_examples: 1442
  download_size: 13871572
  dataset_size: 22211451
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
  - split: validation
    path: data/validation-*
  - split: test
    path: data/test-*
license: cc-by-4.0
task_categories:
- question-answering
language:
- sw
- en
- luo
- lug
- luy
- kik
- yor
- kln
- kin
- lin
- mas
- hau
- zul
- xho
- twi
- fon
- guz
tags:
- african-languages
- QuAD
- Cross-lingual
size_categories:
- 1K<n<10K
---


# AfriQuAD (Multilingual)

This dataset spans across different African languages and also touches on cross-lingual aspects. It can be best used in Question Answering tasks.

```python
from datasets import load_datasets

#load the entire dataset
dataset = load_dataset("theophilusowiti/AfriQuAD")
```