| # Logion: Machine Learning for Greek Philology | |
| The most advanced Ancient Greek BERT model trained to date! Read the paper on [arxiv](https://arxiv.org/abs/2305.01099) by Charlie Cowen-Breen, Creston Brooks, Johannes Haubold, and Barbara Graziosi. | |
| We train a WordPiece tokenizer (with a vocab size of 50,000) on a corpus of over 70 million words of premodern Greek. Using this tokenizer and the same corpus, we train a BERT model. | |
| Further information on this project and code for error detection can be found on [GitHub](https://github.com/charliecb/Logion). | |
| We're adding more models trained with cleaner data and different tokenizations - keep an eye out! | |
| ## 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("cabrooks/LOGION-50k_wordpiece") | |
| model = BertForMaskedLM.from_pretrained("cabrooks/LOGION-50k_wordpiece") | |
| ``` | |
| ## Cite | |
| If you use this model in your research, please cite the paper: | |
| ``` | |
| @inproceedings{logion-base, | |
| author = {Cowen-Breen, Charlie and Brooks, Creston and Haubold, Johannes and Graziosi, Barbara}, | |
| title = {Logion: Machine Learning for Greek Philology}, | |
| year = {2023}, | |
| url = {https://arxiv.org/abs/2305.01099} | |
| } | |
| ``` | |