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README.md
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---
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license: cc-by-nc-sa-4.0
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---
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---
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license: cc-by-nc-sa-4.0
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language:
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- en
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- de
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- fr
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- zh
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- ja
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- ro
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tags:
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- word alignment
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- multilingual
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- translation
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---
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# Model Description
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Refer to [https://github.com/qiyuw/WSPAlign](https://github.com/qiyuw/WSPAlign) and [https://github.com/qiyuw/WSPAlign.InferEval](https://github.com/qiyuw/WSPAlign.InferEval) for details.
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# Qucik Usage
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First clone inference repository:
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```
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git clone https://github.com/qiyuw/WSPAlign.InferEval.git
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```
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Then install the requirements following [https://github.com/qiyuw/WSPAlign.InferEval](https://github.com/qiyuw/WSPAlign.InferEval). For inference only `transformers`, `SpaCy` and `torch` are required.
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Finally, run the following example:
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```
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python inference.py --model_name_or_path qiyuw/WSPAlign-ft-kftt --src_lang ja --src_text="私は猫が好きです。" --tgt_lang en --tgt_text="I like cats."
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```
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Check `inference.py` for details usage.
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# Citation
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Cite our paper if WSPAlign helps your work:
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```bibtex
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@inproceedings{wu-etal-2023-wspalign,
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title = "{WSPA}lign: Word Alignment Pre-training via Large-Scale Weakly Supervised Span Prediction",
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author = "Wu, Qiyu and Nagata, Masaaki and Tsuruoka, Yoshimasa",
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booktitle = "Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)",
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month = jul,
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year = "2023",
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address = "Toronto, Canada",
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publisher = "Association for Computational Linguistics",
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url = "https://aclanthology.org/2023.acl-long.621",
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pages = "11084--11099",
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}
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```
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