| # Logion: Machine Learning for Greek Philology | |
| BERT model trained on largest set of Ancient Greek texts to-date. | |
| Read the ALP paper on [here](https://aclanthology.org/2023.alp-1.20/). | |
| Trained using WordPiece tokenizer (vocab size of 50,000) on a corpus of 70+ million words in pre-modern Greek. | |
| ## How to use | |
| Requirements: | |
| ```python | |
| pip install transformers | |
| ``` | |
| Load the model and tokenizer directly from the HuggingFace Model Hub: | |
| ```python | |
| from transformers import BertTokenizer, BertForMaskedLM | |
| tokenizer = BertTokenizer.from_pretrained("princeton-logion/LOGION-50k_wordpiece") | |
| model = BertForMaskedLM.from_pretrained("princeton-logion/LOGION-50k_wordpiece") | |
| ``` | |
| ## Cite | |
| If you use this model in your research, please cite the paper: | |
| ``` | |
| @inproceedings{cowen-breen-etal-2023-logion, | |
| title = "Logion: Machine-Learning Based Detection and Correction of Textual Errors in {G}reek Philology", | |
| author = "Cowen-Breen, Charlie and | |
| Brooks, Creston and | |
| Graziosi, Barbara and | |
| Haubold, Johannes", | |
| booktitle = "Proceedings of the Ancient Language Processing Workshop", | |
| year = "2023", | |
| url = "https://aclanthology.org/2023.alp-1.20", | |
| pages = "170--178", | |
| } | |
| ``` | |