Nile-Chat: Egyptian Language Models for Arabic and Latin Scripts
Authors: name: Guokan Shang, name: Hadi Abdine, name: Ahmad Chamma, name: Amr Mohamed, name: Mohamed Anwar, name: Abdelaziz Bounhar, name: Omar El Herraoui, name: Preslav Nakov, name: Michalis Vazirgiannis, name: Eric Xing

We introduce Nile-Chat-4B, 3x4B-A6B, and 12B, a collection of LLMs for
Egyptian dialect, uniquely designed to understand and generate texts written in
both Arabic and Latin scripts. Specifically, with Nile-Chat-3x4B-A6B, we
introduce a novel language adaptation approach by leveraging the
Branch-Train-MiX strategy to merge script-specialized experts, into a single
MoE model. Our Nile-Chat models significantly outperform leading multilingual
and Arabic LLMs, such as LLaMa, Jais, and ALLaM, on our newly introduced
Egyptian evaluation benchmarks, which span both understanding and generative
tasks. Notably, our 12B model yields a 14.4% performance gain over
Qwen2.5-14B-Instruct on Latin-script benchmarks. All our resources are publicly
available. We believe this work presents a comprehensive methodology for
adapting LLMs to dual-script languages, addressing an often overlooked aspect
in modern LLM development.