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GlorIA-1.3B-allGlorIA-1.3B-positivealbertina-900m-ptbr-allalbertina-900m-ptbr-positivealbertina-900m-ptpt-allalbertina-900m-ptpt-positive*-all models were fine-tuned with all the data from the training portion of Puntuguese, including negative examples. Meanwhile, the *-positive models were trained only on texts that contain at least one pun sign.AutoModelForSequenceClassification.from_pretrained() method with the subfolder argument.albertina-900m-ptbr-positive, we need the following code:1from transformers import AutoModelForSequenceClassification
2
3model = AutoModelForSequenceClassification.from_pretrained('Superar/Portuguese-Pun-Location',
4 subfolder='albertina-900m-ptbr-positive/checkpoint-500')1@inproceedings{gameiro_etal:epia2024,
2 title = {Sequence Labeling for Pun Location and Detection in {{Portuguese}}},
3 booktitle = {Proceedings of 23rd {{EPIA}} Conference on Artificial Intelligence, {{EPIA}} 2024},
4 author = {Gameiro, Patr{\'{\i}}cia and In{\'a}cio, Marcio and Gon{\c c}alo Oliveira, Hugo and Alves, Ana},
5 year = {2024},
6 pages = {In press},
7 address = {Viana do Castelo, Portugal}
8}