teambits009/Digraphs-Model-Simulation

Swahili is spoken by over 100 million people across East and Central Africa — yet remains vastly underrepresented in AI. This project closes that gap by creating open tools to train, deploy, and simulate models tailored to African linguistics and culture. 🌍 Swahili NLP Model Trainer & Simulation Pipeline A comprehensive project designed to simulate, train, and deploy Swahili language models for natural language understanding, generation, and speech integration. Built for researchers, AI practitioners, and edtech developers focusing on African languages. 📘 Overview This repository contains all components required to build, fine-tune, and simulate Swahili NLP models, including: Custom data ingestion pipelines Preprocessing workflows Model training using transformer architectures Evaluation tools and inference interfaces Voice/text simulation modules (optional) ✨ Why Swahili? Swahili is spoken by over 100 million people across East and Central Africa — yet remains vastly underrepresented in AI. This project closes that gap by creating open tools to train, deploy, and simulate models tailored to African linguistics and culture. 🧩 Features 🧠 Custom NLP model training (BERT, GPT-2, mT5, LLaMA variants) 📚 Multisource Swahili data ingestion (news, YouTube, chat) 🪄 Preprocessing with Swahili-aware tokenization 🎯 Evaluation & visualization dashboard 🔊 Speech-to-text (ASR) + Text-to-speech (TTS) modules (optional) ⚡ Deployable via HuggingFace, TorchScript, or ONNX 🏗️ Project Structure Edit swahili-nlp-simulator/ ├── data/ │ ├── raw/ # Unprocessed Swahili data │ ├── cleaned/ # Tokenized and filtered datasets ├── src/ │ ├── data_pipeline.py # Ingest, clean, and normalize text │ ├── tokenizer.py # Swahili-specific tokenizer (SentencePiece) │ ├── train.py # Model training loop (transformer-based) │ ├── evaluate.py # BLEU, F1, Perplexity metrics │ ├── simulate.py # Interactive chat + simulation environment ├── models/ │ └── checkpoints/ # Trained models & weights ├── notebooks/ │ └── analysis.ipynb # EDA, token stats, sample generation ├── README.md └── requirements.txt 🚀 Getting Started 1. Clone the Repository Edit git …