# 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}
}
```