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
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README.md
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### Multilingual Training Dataset
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| Languages | # Sentences | Source |
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| GRC-ENG | 32.500 | Perseus Digital Library (Iliad, Odyssey, Xenophon, New Testament) |
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| GRC-LAT | 8.200 | [Digital Fragmenta Historicorum Graecorum project](https://www.dfhg-project.org/) |
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| GRC-KAT GRC-ENG GRC-LAT
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### Multilingual Training Dataset
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| Languages | # Sentences | Source |
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| GRC-ENG | 32.500 | Perseus Digital Library (Iliad, Odyssey, Xenophon, New Testament) |
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| GRC-LAT | 8.200 | [Digital Fragmenta Historicorum Graecorum project](https://www.dfhg-project.org/) |
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| GRC-KAT <br>GRC-ENG <br>GRC-LAT<br>GRC-ITA<br>GRC-POR | 4.000 | [UGARIT Translation Alignment Editor](https://ugarit.ialigner.com/ ) |
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