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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}
}
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