# TeenyTinyLlama: open-source tiny language models trained in Brazilian Portuguese

Nicholas Kluge Corrêa1,2, Sophia Falk1, Shiza Fatimah1, Aniket Sen1,
Nythamar Fernandes De Oliveira2
1University of Bonn
2Pontifical Catholic University of Rio Grande do Sul
Paper arXiv Code Hugging Face Demo

## TeenyTinyLlama is a pair of compact models for Brazilian Portuguese text generation. We release them under the permissive Apache 2.0 license on GitHub and Hugging Face for community use and further development.

## Abstract

Large language models (LLMs) have significantly advanced natural language processing, but their progress has yet to be equal across languages. While most LLMs are trained in high-resource languages like English, multilingual models generally underperform monolingual ones. Additionally, aspects of their multilingual foundation sometimes restrict the byproducts they produce, like computational demands and licensing regimes. In this study, we document the development of open-foundation models tailored for use in low-resource settings, their limitations, and their benefits. This is the TeenyTinyLlama pair: two compact models for Brazilian Portuguese text generation. We release them under the permissive Apache 2.0 license on GitHub and Hugging Face for community use and further development.

## BibTeX

    @misc{correa24ttllama,
      doi = {10.1016/j.mlwa.2024.100558},
      url = {https://www.sciencedirect.com/science/article/pii/S2666827024000343},
      title = {TeenyTinyLlama: open-source tiny language models trained in Brazilian Portuguese},
      author = {Corr{\^e}a, Nicholas Kluge and Falk, Sophia and Fatimah, Shiza and Sen, Aniket and De Oliveira, Nythamar},
      journal={Machine Learning With Applications},
      publisher = {Springer},
      year={2024}
    }