BERTabaporu is a Brazilian Portuguese BERT model in the Twitter domain. The model has been built from a collection of 238 million tweets written by over 100 thousand unique Twitter users, and conveying over 2.9 billion tokens in total.
1from transformers import AutoTokenizer # Or BertTokenizer
2from transformers import AutoModelForPreTraining # Or BertForPreTraining for loading pretraining heads
3from transformers import AutoModel # or BertModel, for BERT without pretraining heads
4model = AutoModelForPreTraining.from_pretrained('pablocosta/bertabaporu-base-uncased')
5tokenizer = AutoTokenizer.from_pretrained('pablocosta/bertabaporu-base-uncased')
@inproceedings{costa-etal-2023-bertabaporu,
title = "{BERT}abaporu: Assessing a Genre-Specific Language Model for {P}ortuguese {NLP}",
author = "Costa, Pablo Botton and
Pavan, Matheus Camasmie and
Santos, Wesley Ramos and
Silva, Samuel Caetano and
Paraboni, Ivandr{'e}",
editor = "Mitkov, Ruslan and
Angelova, Galia",
booktitle = "Proceedings of the 14th International Conference on Recent Advances in Natural Language Processing",
month = sep,
year = "2023",
address = "Varna, Bulgaria",
publisher = "INCOMA Ltd., Shoumen, Bulgaria",
url = "
https://aclanthology.org/2023.ranlp-1.24",
pages = "217--223",
abstract = "Transformer-based language models such as Bidirectional Encoder Representations from Transformers (BERT) are now mainstream in the NLP field, but extensions to languages other than English, to new domains and/or to more specific text genres are still in demand. In this paper we introduced BERTabaporu, a BERT language model that has been pre-trained on Twitter data in the Brazilian Portuguese language. The model is shown to outperform the best-known general-purpose model for this language in three Twitter-related NLP tasks, making a potentially useful resource for Portuguese NLP in general.",
}
