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