Advancing Generative AI for Portuguese with Open Decoder Gervásio PT*

Rodrigo Santos, João Ricardo Silva, Luís Gomes, João Rodrigues, António Branco


Abstract
To advance the neural decoding of Portuguese, in this paper we present a fully open Transformer-based, instruction-tuned decoder model that sets a new state of the art in this respect. To develop this decoder, which we named Gervásio PT*, a strong LLaMA 2 7B model was used as a starting point, and its further improvement through additional training was done over language resources that include new instruction data sets of Portuguese prepared for this purpose, which are also contributed in this paper. All versions of Gervásio are open source and distributed for free under an open license, including for either research or commercial usage, and can be run on consumer-grade hardware, thus seeking to contribute to the advancement of research and innovation in language technology for Portuguese.
Anthology ID:
2024.sigul-1.3
Volume:
Proceedings of the 3rd Annual Meeting of the Special Interest Group on Under-resourced Languages @ LREC-COLING 2024
Month:
May
Year:
2024
Address:
Torino, Italia
Editors:
Maite Melero, Sakriani Sakti, Claudia Soria
Venues:
SIGUL | WS
SIG:
Publisher:
ELRA and ICCL
Note:
Pages:
16–26
Language:
URL:
https://aclanthology.org/2024.sigul-1.3
DOI:
Bibkey:
Cite (ACL):
Rodrigo Santos, João Ricardo Silva, Luís Gomes, João Rodrigues, and António Branco. 2024. Advancing Generative AI for Portuguese with Open Decoder Gervásio PT*. In Proceedings of the 3rd Annual Meeting of the Special Interest Group on Under-resourced Languages @ LREC-COLING 2024, pages 16–26, Torino, Italia. ELRA and ICCL.
Cite (Informal):
Advancing Generative AI for Portuguese with Open Decoder Gervásio PT* (Santos et al., SIGUL-WS 2024)
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PDF:
https://aclanthology.org/2024.sigul-1.3.pdf