AI 모델 라이브러리

This model is part of the OPUS-MT project, an effort to make neural machine translation models widely available and accessible for many languages in the world. All models are originally trained using the amazing framework of Marian NMT, an efficient NMT implementation written in pure C++. The models have been converted to pyTorch using the transformers library by huggingface. Training data is taken from OPUS and training pipelines use the procedures of OPUS-MT-train. **Model Description:** - **Developed by:** Language Technology Research Group at the University of Helsinki - **Model Type:** Translation (transformer-big) - **Release**: 2022-07-28 - **License:** CC-BY-4.0 - **Language(s):** - Source Language(s): - Target Language(s): - Valid Target Language Labels: - **Original Model**: opusTCv20210807-sepvoc_transformer-big_2022-07-28.zip - **Resources for more information:** - OPUS-MT-train GitHub Repo - More information about released models for this language pair: OPUS-MT eng-kor README - More information about MarianNMT models in the transformers library - [Tatoeba Translation Challenge](https://github.com/Helsinki-NLP/Tatoeba-Challenge/ This is a multilingual translation model with multiple target languages. A sentence initial language token is required in the form of `>>id ><<` **CONTENT WARNING: Readers should be aware that the model is trained on various public data sets that may contain content that is disturbing, offensive, and can propagate historical and current stereotypes.**

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요금 미확인멀티모달 및 채널 요금 별도 확인

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opus-mt-tc-big-en-lt

Helsinki-NLP

基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。

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요금 미확인멀티모달 및 채널 요금 별도 확인

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opus-mt-tc-big-en-lv

Helsinki-NLP

基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。

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입력 텍스트→ 출력 텍스트

요금 미확인멀티모달 및 채널 요금 별도 확인

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비교 추가출처 / 문서 ↗

opus-mt-tc-big-en-pt

Helsinki-NLP

This model is part of the OPUS-MT project, an effort to make neural machine translation models widely available and accessible for many languages in the world. All models are originally trained using the amazing framework of Marian NMT, an efficient NMT implementation written in pure C++. The models have been converted to pyTorch using the transformers library by huggingface. Training data is taken from OPUS and training pipelines use the procedures of OPUS-MT-train. The work is supported by the European Language Grid as pilot project 2866, by the FoTran project, funded by the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (grant agreement No 771113), and the MeMAD project, funded by the European Union’s Horizon 2020 Research and Innovation Programme under grant agreement No 780069. We are also grateful for the generous computational resources and IT infrastructure provided by CSC -- IT Center for Science, Finland.

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입력 텍스트→ 출력 텍스트

요금 미확인멀티모달 및 채널 요금 별도 확인

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비교 추가출처 / 문서 ↗

opus-mt-tc-big-en-ro

Helsinki-NLP

基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。

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번역

입력 텍스트→ 출력 텍스트

요금 미확인멀티모달 및 채널 요금 별도 확인

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opus-mt-tc-big-en-tr

Helsinki-NLP

Neural machine translation model for translating from English (en) to Turkish (tr). This model is part of the OPUS-MT project, an effort to make neural machine translation models widely available and accessible for many languages in the world. All models are originally trained using the amazing framework of Marian NMT, an efficient NMT implementation written in pure C++. The models have been converted to pyTorch using the transformers library by huggingface. Training data is taken from OPUS and training pipelines use the procedures of OPUS-MT-train. * Publications: OPUS-MT – Building open translation services for the World and The Tatoeba Translation Challenge – Realistic Data Sets for Low Resource and Multilingual MT (Please, cite if you use this model.)

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입력 텍스트→ 출력 텍스트

요금 미확인멀티모달 및 채널 요금 별도 확인

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opus-mt-tc-big-en-zle

Helsinki-NLP

基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。

번역

입력 텍스트→ 출력 텍스트

요금 미확인멀티모달 및 채널 요금 별도 확인

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비교 추가출처 / 문서 ↗

opus-mt-tc-big-fi-en

Helsinki-NLP

基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。

번역

입력 텍스트→ 출력 텍스트

요금 미확인멀티모달 및 채널 요금 별도 확인

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비교 추가출처 / 문서 ↗

opus-mt-tc-big-fr-en

Helsinki-NLP

基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。

번역

입력 텍스트→ 출력 텍스트

요금 미확인멀티모달 및 채널 요금 별도 확인

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opus-mt-tc-big-gmq-en

Helsinki-NLP

基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。

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입력 텍스트→ 출력 텍스트

요금 미확인멀티모달 및 채널 요금 별도 확인

자세히 보기 ↗

비교 추가출처 / 문서 ↗

opus-mt-tc-big-he-en

Helsinki-NLP

This model is part of the OPUS-MT project, an effort to make neural machine translation models widely available and accessible for many languages in the world. All models are originally trained using the amazing framework of Marian NMT, an efficient NMT implementation written in pure C++. The models have been converted to pyTorch using the transformers library by huggingface. Training data is taken from OPUS and training pipelines use the procedures of OPUS-MT-train. The work is supported by the European Language Grid as pilot project 2866, by the FoTran project, funded by the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (grant agreement No 771113), and the MeMAD project, funded by the European Union’s Horizon 2020 Research and Innovation Programme under grant agreement No 780069. We are also grateful for the generous computational resources and IT infrastructure provided by CSC -- IT Center for Science, Finland.

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입력 텍스트→ 출력 텍스트

요금 미확인멀티모달 및 채널 요금 별도 확인

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opus-mt-tc-big-it-en

Helsinki-NLP

基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。

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요금 미확인멀티모달 및 채널 요금 별도 확인

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opus-mt-tc-big-itc-itc

Helsinki-NLP

基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。

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요금 미확인멀티모달 및 채널 요금 별도 확인

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비교 추가출처 / 문서 ↗

opus-mt-tc-big-ko-en

Helsinki-NLP

- Model Details - Uses - Risks, Limitations and Biases - How to Get Started With the Model - Training - Evaluation - Citation Information - Acknowledgements Neural machine translation model for translating from Korean (ko) to English (en). This model is part of the OPUS-MT project, an effort to make neural machine translation models widely available and accessible for many languages in the world. All models are originally trained using the amazing framework of Marian NMT, an efficient NMT implementation written in pure C++. The models have been converted to pyTorch using the transformers library by huggingface. Training data is taken from OPUS and training pipelines use the procedures of OPUS-MT-train. **Model Description:** - **Developed by:** Language Technology Research Group at the University of Helsinki - **Model Type:** Translation (transformer-big) - **Release**: 2022-07-28 - **License:** CC-BY-4.0 - **Language(s):** - Source Language(s): kor - Target Language(s): eng - **Original Model**: opusTCv20210807-sepvoc_transformer-big_2022-07-28.zip - **Resources for more information:** - OPUS-MT-train GitHub Repo - More information about released models for this language pair: OPUS-MT kor-eng README - More information about MarianNMT models in the transformers library - [Tatoeba Translation Challenge](https://github.com/Helsinki-NLP/Tatoeba-Challenge/

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요금 미확인멀티모달 및 채널 요금 별도 확인

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opus-mt-tc-big-lt-en

Helsinki-NLP

基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。

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번역

입력 텍스트→ 출력 텍스트

요금 미확인멀티모달 및 채널 요금 별도 확인

자세히 보기 ↗

비교 추가출처 / 문서 ↗

opus-mt-tc-big-sh-en

Helsinki-NLP

This model is part of the OPUS-MT project, an effort to make neural machine translation models widely available and accessible for many languages in the world. All models are originally trained using the amazing framework of Marian NMT, an efficient NMT implementation written in pure C++. The models have been converted to pyTorch using the transformers library by huggingface. Training data is taken from OPUS and training pipelines use the procedures of OPUS-MT-train. The work is supported by the European Language Grid as pilot project 2866, by the FoTran project, funded by the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (grant agreement No 771113), and the MeMAD project, funded by the European Union’s Horizon 2020 Research and Innovation Programme under grant agreement No 780069. We are also grateful for the generous computational resources and IT infrastructure provided by CSC -- IT Center for Science, Finland.

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번역

입력 텍스트→ 출력 텍스트

요금 미확인멀티모달 및 채널 요금 별도 확인

자세히 보기 ↗

비교 추가출처 / 문서 ↗

opus-mt-tc-big-tr-en

Helsinki-NLP

This model is part of the OPUS-MT project, an effort to make neural machine translation models widely available and accessible for many languages in the world. All models are originally trained using the amazing framework of Marian NMT, an efficient NMT implementation written in pure C++. The models have been converted to pyTorch using the transformers library by huggingface. Training data is taken from OPUS and training pipelines use the procedures of OPUS-MT-train. The work is supported by the European Language Grid as pilot project 2866, by the FoTran project, funded by the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (grant agreement No 771113), and the MeMAD project, funded by the European Union’s Horizon 2020 Research and Innovation Programme under grant agreement No 780069. We are also grateful for the generous computational resources and IT infrastructure provided by CSC -- IT Center for Science, Finland.

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번역

입력 텍스트→ 출력 텍스트

요금 미확인멀티모달 및 채널 요금 별도 확인

자세히 보기 ↗

비교 추가출처 / 문서 ↗