koneke55/BPE_Tokenizer_Bamanakan_language

# 🐘 Bambara BPE Tokenizer > A clean, research-grade **Byte Pair Encoding (BPE)** tokenizer built from scratch for the **Bambara** language. > Designed for linguists, NLP researchers, and developers working on Mande language processing. > Fully Linux-friendly and ready to run locally or in Google Colab. --- ## 🧩 Overview The **Bambara BPE Tokenizer** is a lightweight implementation of the Byte Pair Encoding algorithm. It allows you to: - Train subword tokenization models on Bambara text - Handle Bambara diacritics (`ɛ`, `ɔ`, `ŋ`, `ɲ`) - Encode and decode text into consistent subword units - Use it as a standalone module or integrate into a larger NLP pipeline --- ## 🧠 Conceptual Illustration Below is a simple visual explanation of how the tokenizer works: > Example: > `"Bamanankan"` → `"Ba"` `"ma"` `"nan"` `"kan"` This shows how the tokenizer learns to break a Bambara word into subword components — a key step for efficient NLP modeling on low-resource languages. --- ## 📁 Project Structure bambara-bpe-tokenizer/ ├── README.md # Project documentation ├── requirements.txt # Dependencies list ├── LICENSE # MIT License ├── data/ # Example corpus files │ └── sample_corpus.txt ├── bambara_bpe_tokenizer/ # Core Python package │ ├── init.py │ └── tokenizer.py ├── examples/ # Demos and notebooks │ └── demo_colab.ipynb ├── docs/ # Documentation & diagrams │ └── bpe_diagram.png └── tests/ # Unit tests └── test_tokenizer.py --- ## ⚙️ Installation (Linux / macOS) ### 1️⃣ Clone the repository ```bash git clone github.com cd bambara-bpe-tokenizer 2️⃣ (Optional) Create and activate a virtual environment bash Copy code python3 -m venv .venv source .venv/bin/activate 3️⃣ Install dependencies bash Copy code pip install -r requirements.txt 4️⃣ Install the package bash Copy code pip install -e . 🚀 Quick Start (Python) python Copy code from bambara_ …