license: cc-by-sa-4.0
pretty_name: Tigre language
language:
- tig
Tigre Low-Resource Language Resource Collection
Overview
This repository introduces the Monolingual Text component of the Tigre language resource collection. Tigre is an under-resourced South Semitic language within the Afro-Asiatic family. This dataset provides a large, clean text corpus essential for training foundational models such as Language Models (LMs) and word embeddings. The goal of Tigre-Data 1.0 is to accelerate research in low-resource NLP and morphologically rich language modeling.
Included Data & Statistics
Data Modalities
This repository contains only the Monolingual Text data modality.
Dataset Statistics
The corpus was tokenized using a simple whitespace tokenizer to determine the core metrics below.
| Statistic | Value |
|---|---|
| Total Number of Examples (Rows) | 490,032 |
| Total Number of Tokens | 14,700,960 |
| Vocabulary Size (Unique Tokens) | 760,384 |
| Average Example Length | 30.00 tokens/row |
Dataset Structure
The dataset is provided in the Parquet format, which is easily streamed and loaded using the Hugging Face datasets library.
tigre-data-monolingual-text/
├── README.md
├── data.parquet
└── arrow_format/
└── train/
├── data-00000-of-00001.arrow
├── dataset_info.json
└── state.json
Data Provenance & Methodology
Sources
The monolingual text corpus was compiled from diverse sources to maximize coverage:
- Books
- News articles
- Web content
- Wikipedia
Data Curation & Preprocessing
- Preprocessing: The data underwent a light cleanup of data to remove non text binaries.
- Orthographic Normalization: The original corpus was normalized to ensure consistent Ge'ez script usage.
- Text Cleaning: Steps such as deduplication and boilerplate removal were applied to improve corpus quality (details available in the associated data paper).
Bias, Risks & Known Limitations
The data collection process was designed to be broad; however, inherited biases from the original sources are present:
- Domain Bias: The sources (news articles, history books, poems, culture-related texts) mean the corpus may overrepresent formal and historical language and underrepresent informal or conversational Tigre.
- Linguistic Bias: Any inherent orthographic variation or dialectal representation present in the original source materials is inherited by this dataset.
How to Download & Load the Dataset
The dataset can be easily loaded using the Hugging Face Hub client library:
from datasets import load_dataset
dataset_name = "BeitTigreAI/tigre-data-monolingual-text"
# Load the full dataset (the default split is 'train')
ds = load_dataset(dataset_name, split="train")
# Example: Display the number of rows and the first example
print(f"Total rows loaded: {len(ds)}")
print(ds[0])
```python
## Licensing
CC-BY-SA-4.0
## Citation
If you use this resource in your work, please cite the repository by referencing its Hugging Face entry:
### Recommended Citation Format:
- Repository Name: Tigre Monolingual Text Dataset
- Organization: BeitTigreAI
- URL: https://huggingface.co/datasets/BeitTigreAI/tigre-data-monolingual-text