Logion: Machine Learning for Greek Philology

The most advanced Ancient Greek BERT model trained to date! Read the paper on arxiv 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.

We're adding more models trained with cleaner data and different tokenizations - keep an eye out!

How to use

Requirements:

pip install transformers

Load the model and tokenizer directly from the HuggingFace Model Hub:

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:

@misc{logion-base,
      title={Logion: Machine Learning for Greek Philology}, 
      author={Cowen-Breen, C. and Brooks, C. and Haubold, J. and Graziosi, B.},
      year={2023},
      eprint={2305.01099},
      archivePrefix={arXiv},
      primaryClass={cs.CL}
}