---
license: apache-2.0
task_categories:
- text-generation
tags:
- legal
size_categories:
- 10M<n<100M
---
# Swahili Text Dataset

## Overview

This dataset contains a comprehensive collection of Swahili text data, derived from the [AfriBERTa Corpus](https://huggingface.co/datasets/castorini/afriberta-corpus). It provides a rich resource for natural language processing tasks focused on the Swahili language.

## Dataset Details

- **Source**: [AfriBERTa Corpus](https://huggingface.co/datasets/castorini/afriberta-corpus) (Swahili subset)
- **Language**: Swahili
- **Size**: [Insert total number of samples here]
- **Format**: Hugging Face Dataset

## Content

The dataset consists of two main columns:

1. `id`: A unique identifier for each text entry
2. `text`: The Swahili text content

## Usage

You can load this dataset using the Hugging Face `datasets` library:

```python
from datasets import load_dataset

dataset = load_dataset("[Your_HuggingFace_Username]/[Your_Dataset_Name]")
```

Replace `[Your_HuggingFace_Username]` and `[Your_Dataset_Name]` with the appropriate values for your uploaded dataset.

## Data Fields

- `id`: string
- `text`: string

## Data Splits

This dataset combines training and test splits from the original AfriBERTa Corpus. The data has been shuffled with a fixed seed (42) to ensure reproducibility.

## Dataset Creation

This dataset was created by:

1. Loading the Swahili subset of the AfriBERTa Corpus
2. Concatenating the training and test splits
3. Shuffling the combined dataset
4. Extracting the 'id' and 'text' fields

## Intended Uses

This dataset can be used for various natural language processing tasks involving the Swahili language, such as:

- Language modeling
- Text classification
- Named entity recognition
- Machine translation (as a source or target language)
- Sentiment analysis
- And more...

## Limitations

- The dataset is limited to the content available in the original AfriBERTa Corpus.
- It may not represent all dialects or variations of the Swahili language.
- The quality and accuracy of the text content depend on the original data source.

## Citation

If you use this dataset, please cite the original AfriBERTa Corpus:

```
@inproceedings{ogueji-etal-2021-small,
    title = "Small Data? No Problem! Exploring the Viability of Pretrained Multilingual Language Models for Low-resourced Languages",
    author = "Ogueji, Kelechi  and
      Zhu, Yuxin  and
      Lin, Jimmy",
    booktitle = "Proceedings of the 1st Workshop on Multilingual Representation Learning",
    month = nov,
    year = "2021",
    address = "Punta Cana, Dominican Republic",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/2021.mrl-1.11",
    pages = "116--126",
}
```

## Licensing Information

This dataset is derived from the AfriBERTa Corpus. For usage terms and conditions, please refer to the [original dataset's license](https://huggingface.co/datasets/castorini/afriberta-corpus).

## Contact

If you have questions or comments about this specific version of the dataset, please open an issue in this repository or contact [ronleon76@gmail.com].

---

Dataset created and curated by [AdeptSchneider].
Last updated: [09/10/2024]