TeenyTinyLlama: open-source tiny language models trained in Brazilian Portuguese
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arXiv
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| Main Authors: | , , , , |
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| Format: | Preprint |
| Published: |
2024
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| _version_ | 1866913353564160000 |
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| author | Corrêa, Nicholas Kluge Falk, Sophia Fatimah, Shiza Sen, Aniket de Oliveira, Nythamar |
| author_facet | Corrêa, Nicholas Kluge Falk, Sophia Fatimah, Shiza Sen, Aniket de Oliveira, Nythamar |
| contents | 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. See https://github.com/Nkluge-correa/TeenyTinyLlama |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2401_16640 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | TeenyTinyLlama: open-source tiny language models trained in Brazilian Portuguese Corrêa, Nicholas Kluge Falk, Sophia Fatimah, Shiza Sen, Aniket de Oliveira, Nythamar Computation and Language Machine Learning 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. See https://github.com/Nkluge-correa/TeenyTinyLlama |
| title | TeenyTinyLlama: open-source tiny language models trained in Brazilian Portuguese |
| topic | Computation and Language Machine Learning |
| url | https://arxiv.org/abs/2401.16640 |