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---
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.
```text
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:
```python
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
````
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