| datasets: | |
| - lst20 | |
| language: | |
| - th | |
| widget: | |
| - text: วัน ที่ _ 12 _ มีนาคม นี้ _ ฉัน จะ ไป เที่ยว วัดพระแก้ว _ ที่ กรุงเทพ | |
| library_name: transformers | |
| <!-- # HoogBERTa | |
| This repository includes the Thai pretrained language representation (HoogBERTa_base) and the fine-tuned model for multitask sequence labeling. --> | |
| # Documentation | |
| ## Prerequisite | |
| Since we use subword-nmt BPE encoding, input needs to be pre-tokenize using [BEST](https://huggingface.co/datasets/best2009) standard before inputting into HoogBERTa | |
| ``` | |
| pip install attacut | |
| ``` | |
| # Citation | |
| Please cite as: | |
| ``` bibtex | |
| @inproceedings{porkaew2021hoogberta, | |
| title = {HoogBERTa: Multi-task Sequence Labeling using Thai Pretrained Language Representation}, | |
| author = {Peerachet Porkaew, Prachya Boonkwan and Thepchai Supnithi}, | |
| booktitle = {The Joint International Symposium on Artificial Intelligence and Natural Language Processing (iSAI-NLP 2021)}, | |
| year = {2021}, | |
| address={Online} | |
| } | |
| ``` | |
| Download full-text [PDF](https://drive.google.com/file/d/1hwdyIssR5U_knhPE2HJigrc0rlkqWeLF/view?usp=sharing) | |
| Check out the code on [Github](https://github.com/lstnlp/HoogBERTa) |