Instructions to use UGARIT/grc-alignment with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use UGARIT/grc-alignment with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="UGARIT/grc-alignment")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("UGARIT/grc-alignment") model = AutoModelForMaskedLM.from_pretrained("UGARIT/grc-alignment") - Notebooks
- Google Colab
- Kaggle
| license: cc-by-4.0 | |
| # Automatic Translation Alignment of Ancient Greek Texts | |
| GRC-ALIGNMENT model is an XLM-RoBERTa-based model, fine-tuned for automatic multilingual text alignment at the word level. | |
| The model is trained on 12 million monolingual ancient Greek tokens with Masked Language Model (MLM) training objective. Further, the model is fine-tuned on 45k parallel sentences, mainly in ancient Greek-English, Greek-Latin, and Greek-Georgian. | |
| ### Multilingual Training Dataset | |
| | Languages |Sentences | Source | | |
| |:---------------------------------------|:-----------:|:--------------------------------------------------------------------------------| | |
| | GRC-ENG | 32.500 | Perseus Digital Library (Iliad, Odyssey, Xenophon, New Testament) | | |
| | GRC-LAT | 8.200 | [Digital Fragmenta Historicorum Graecorum project](https://www.dfhg-project.org/) | | |
| | GRC-KAT <br>GRC-ENG <br>GRC-LAT<br>GRC-ITA<br>GRC-POR | 4.000 | [UGARIT Translation Alignment Editor](https://ugarit.ialigner.com/ ) | | |
| ### Model Performance | |
| | Languages | Alignment Error Rate | | |
| |:---------:|:--------------------:| | |
| | GRC-ENG | 19.73% (IterMax) | | |
| | GRC-POR | 23.91% (IterMax) | | |
| | GRC-LAT | 10.60% (ArgMax) | | |
| The gold standard datasets are available on [Github](https://github.com/UgaritAlignment/Alignment-Gold-Standards). | |
| If you use this model, please cite our papers: | |
| <pre> | |
| @InProceedings{yousef-EtAl:2022:LREC, | |
| author = {Yousef, Tariq and Palladino, Chiara and Shamsian, Farnoosh and d’Orange Ferreira, Anise and Ferreira dos Reis, Michel}, | |
| title = {An automatic model and Gold Standard for translation alignment of Ancient Greek}, | |
| booktitle = {Proceedings of the Language Resources and Evaluation Conference}, | |
| month = {June}, | |
| year = {2022}, | |
| address = {Marseille, France}, | |
| publisher = {European Language Resources Association}, | |
| pages = {5894--5905}, | |
| url = {https://aclanthology.org/2022.lrec-1.634} | |
| } | |
| @InProceedings{yousef-EtAl:2022:LT4HALA2022, | |
| author = {Yousef, Tariq and Palladino, Chiara and Wright, David J. and Berti, Monica}, | |
| title = {Automatic Translation Alignment for Ancient Greek and Latin}, | |
| booktitle = {Proceedings of the Second Workshop on Language Technologies for Historical and Ancient Languages}, | |
| month = {June}, | |
| year = {2022}, | |
| address = {Marseille, France}, | |
| publisher = {European Language Resources Association}, | |
| pages = {101--107}, | |
| url = {https://aclanthology.org/2022.lt4hala2022-1.14} | |
| } | |
| </pre> |