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--- |
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license: apache-2.0 |
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language: |
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- en |
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- zh |
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- ja |
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- fr |
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- es |
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- it |
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- pt |
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tags: |
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- generative translation |
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- large language model |
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- LLaMA |
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metrics: |
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- bleu |
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pipeline_tag: text-generation |
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datasets: |
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- PeacefulData/HypoTranslate |
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--- |
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This repo releases the trained LLaMA-adapter weights in paper "GenTranslate: Large Language Models are Generative Multilingual Speech and Machine Translators". |
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**Code:** https://github.com/YUCHEN005/GenTranslate |
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**Data:** https://huggingface.co/datasets/PeacefulData/HypoTranslate |
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**Model:** This repo |
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***Filename format:*** [data\_source]\_[src\_language\_code]\_[tgt\_language\_code]\_[task].pth |
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e.g. covost2_ar_en_st.pth |
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***Note:*** |
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- Language code look-up: Table 15 & 17 in https://arxiv.org/pdf/2402.06894.pdf |
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- Source/target language refers to the translation task, so that the N-best hypotheses and ground-truth transcription are both in target language |
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- For speech translation datasets (FLEURS, CoVoST-2, MuST-C), the task ID "mt" denotes cascaded ASR+MT system |
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If you consider this work would be related or useful for your research, please kindly consider to cite the work below. Thank you. |
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```bib |
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@inproceedings{hu2024gentranslate, |
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title = "GenTranslate: Large Language Models are Generative Multilingual Speech and Machine Translators", |
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author = "Hu, Yuchen and Chen, Chen and Yang, Chao-Han Huck and Li, Ruizhe and Zhang, Dong and Chen, Zhehuai and Chng, Eng Siong", |
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booktitle = "Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)", |
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publisher = "Association for Computational Linguistics", |
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year = "2024" |
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} |
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``` |
