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---
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---
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language:
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- ja
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thumbnail: "https://raw.githubusercontent.com/megagonlabs/ginza/static/docs/images/GiNZA_logo_4c_s.png"
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tags:
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- PyTorch
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- Transformers
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- spaCy
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- ELECTRA
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- GiNZA
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- mC4
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- UD_Japanese-BCCWJ
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- GSK2014-A
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- ja
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- MIT
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license: "mit"
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datasets:
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- mC4
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- UD_Japanese_BCCWJ-r2.8
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- GSK2014-A(2019)
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metrics:
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- UAS
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- LAS
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- UPOS
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---
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# transformers-ud-japanese-electra-ginza-520 (sudachitra-wordpiece, mC4 Japanese)
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This is an [ELECTRA](https://github.com/google-research/electra) model pretrained on approximately 200M Japanese sentences extracted from the [mC4](https://huggingface.co/datasets/mc4) and finetuned by [spaCy v3](https://spacy.io/usage/v3) on [UD\_Japanese\_BCCWJ r2.8](https://universaldependencies.org/treebanks/ja_bccwj/index.html).
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The base pretrain model is [megagonlabs/transformers-ud-japanese-electra-base-discrimininator](https://huggingface.co/megagonlabs/transformers-ud-japanese-electra-base-discriminator).
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The entire spaCy v3 model is distributed as a python package named [`ja_ginza_electra`](https://pypi.org/project/ja-ginza-electra/) from PyPI along with [`GiNZA v5`](https://github.com/megagonlabs/ginza) which provides some custom pipeline components to recognize the Japanese bunsetu-phrase structures.
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Try running it as below:
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```console
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$ pip install ginza ja_ginza_electra
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$ ginza
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```
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## Licenses
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The models are distributed under the terms of the [MIT License](https://opensource.org/licenses/mit-license.php).
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## Acknowledgments
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This model is permitted to be published under the `MIT License` under a joint research agreement between NINJAL (National Institute for Japanese Language and Linguistics) and Megagon Labs Tokyo.
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## Citations
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- [mC4](https://huggingface.co/datasets/mc4)
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Contains information from `mC4` which is made available under the [ODC Attribution License](https://opendatacommons.org/licenses/by/1-0/).
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```
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@article{2019t5,
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author = {Colin Raffel and Noam Shazeer and Adam Roberts and Katherine Lee and Sharan Narang and Michael Matena and Yanqi Zhou and Wei Li and Peter J. Liu},
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title = {Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer},
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journal = {arXiv e-prints},
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year = {2019},
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archivePrefix = {arXiv},
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eprint = {1910.10683},
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}
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```
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- [UD\_Japanese\_BCCWJ r2.8](https://universaldependencies.org/treebanks/ja_bccwj/index.html)
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```
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Asahara, M., Kanayama, H., Tanaka, T., Miyao, Y., Uematsu, S., Mori, S.,
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Matsumoto, Y., Omura, M., & Murawaki, Y. (2018).
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Universal Dependencies Version 2 for Japanese.
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In LREC-2018.
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```
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- [GSK2014-A(2019)](https://www.gsk.or.jp/catalog/gsk2014-a/)
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