
# transformers-ud-japanese-electra-ginza-510 (sudachitra-wordpiece, mC4 Japanese)

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).

The base pretrain model is [megagonlabs/transformers-ud-japanese-electra-base-discrimininator](https://huggingface.co/megagonlabs/transformers-ud-japanese-electra-base-discriminator).

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.
Try running it as below:
```console
$ pip install ginza ja_ginza_electra
$ ginza
```

## Licenses

The models are distributed under the terms of the [MIT License](https://opensource.org/licenses/mit-license.php).

## Acknowledgments

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.

## Citations
- [mC4](https://huggingface.co/datasets/mc4)

Contains information from `mC4` which is made available under the [ODC Attribution License](https://opendatacommons.org/licenses/by/1-0/).
```
@article{2019t5,
    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},
    title = {Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer},
    journal = {arXiv e-prints},
    year = {2019},
    archivePrefix = {arXiv},
    eprint = {1910.10683},
}
```

- [UD\_Japanese\_BCCWJ r2.8](https://universaldependencies.org/treebanks/ja_bccwj/index.html)

```
Asahara, M., Kanayama, H., Tanaka, T., Miyao, Y., Uematsu, S., Mori, S.,
Matsumoto, Y., Omura, M., & Murawaki, Y. (2018).
Universal Dependencies Version 2 for Japanese.
In LREC-2018.
```

- [GSK2014-A(2019)](https://www.gsk.or.jp/catalog/gsk2014-a/)

{"language": ["ja"], "license": "mit", "tags": ["PyTorch", "Transformers", "spaCy", "ELECTRA", "GiNZA", "mC4", "UD_Japanese-BCCWJ", "GSK2014-A", "ja", "MIT"], "datasets": ["mC4", "UD_Japanese_BCCWJ r2.8", "GSK2014-A(2019)"], "metrics": ["UAS", "LAS", "UPOS"], "thumbnail": "https://raw.githubusercontent.com/megagonlabs/ginza/static/docs/images/GiNZA_logo_4c_s.png"}
transformers pytorch electra feature-extraction PyTorch Transformers spaCy ELECTRA GiNZA mC4 UD_Japanese-BCCWJ GSK2014-A ja MIT arxiv:1910.10683 license:mit endpoints_compatible region:us
TAGS
#transformers #pytorch #electra #feature-extraction #PyTorch #Transformers #spaCy #ELECTRA #GiNZA #mC4 #UD_Japanese-BCCWJ #GSK2014-A #ja #MIT #arxiv-1910.10683 #license-mit #endpoints_compatible #region-us 


# transformers-ud-japanese-electra-ginza-510 (sudachitra-wordpiece, mC4 Japanese)

This is an ELECTRA model pretrained on approximately 200M Japanese sentences extracted from the mC4 and finetuned by spaCy v3 on UD\_Japanese\_BCCWJ r2.8.

The base pretrain model is megagonlabs/transformers-ud-japanese-electra-base-discrimininator.

The entire spaCy v3 model is distributed as a python package named 'ja_ginza_electra' from PyPI along with 'GiNZA v5' which provides some custom pipeline components to recognize the Japanese bunsetu-phrase structures.
Try running it as below:


## Licenses

The models are distributed under the terms of the MIT License.

## Acknowledgments

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.

s
- mC4

Contains information from 'mC4' which is made available under the ODC Attribution License.


- UD\_Japanese\_BCCWJ r2.8



- GSK2014-A(2019)

# transformers-ud-japanese-electra-ginza-510 (sudachitra-wordpiece, mC4 Japanese)

This is an ELECTRA model pretrained on approximately 200M Japanese sentences extracted from the mC4 and finetuned by spaCy v3 on UD\_Japanese\_BCCWJ r2.8.

The base pretrain model is megagonlabs/transformers-ud-japanese-electra-base-discrimininator.

The entire spaCy v3 model is distributed as a python package named 'ja_ginza_electra' from PyPI along with 'GiNZA v5' which provides some custom pipeline components to recognize the Japanese bunsetu-phrase structures.
Try running it as below: ## Licenses

The models are distributed under the terms of the MIT License. ## Acknowledgments

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.

s
- mC4

Contains information from 'mC4' which is made available under the ODC Attribution License.


- UD\_Japanese\_BCCWJ r2.8



- GSK2014-A(2019)
TAGS
#transformers #pytorch #electra #feature-extraction #PyTorch #Transformers #spaCy #ELECTRA #GiNZA #mC4 #UD_Japanese-BCCWJ #GSK2014-A #ja #MIT #arxiv-1910.10683 #license-mit #endpoints_compatible #region-us 
 # transformers-ud-japanese-electra-ginza-510 (sudachitra-wordpiece, mC4 Japanese)

This is an ELECTRA model pretrained on approximately 200M Japanese sentences extracted from the mC4 and finetuned by spaCy v3 on UD\_Japanese\_BCCWJ r2.8.

The base pretrain model is megagonlabs/transformers-ud-japanese-electra-base-discrimininator.

The entire spaCy v3 model is distributed as a python package named 'ja_ginza_electra' from PyPI along with 'GiNZA v5' which provides some custom pipeline components to recognize the Japanese bunsetu-phrase structures.
Try running it as below: ## Licenses

The models are distributed under the terms of the MIT License. ## Acknowledgments

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.

s
- mC4

Contains information from 'mC4' which is made available under the ODC Attribution License.


- UD\_Japanese\_BCCWJ r2.8



- GSK2014-A(2019)
TAGS
#transformers #pytorch #electra #feature-extraction #PyTorch #Transformers #spaCy #ELECTRA #GiNZA #mC4 #UD_Japanese-BCCWJ #GSK2014-A #ja #MIT #arxiv-1910.10683 #license-mit #endpoints_compatible #region-us 
# transformers-ud-japanese-electra-ginza-510 (sudachitra-wordpiece, mC4 Japanese)

This is an ELECTRA model pretrained on approximately 200M Japanese sentences extracted from the mC4 and finetuned by spaCy v3 on UD\_Japanese\_BCCWJ r2.8.

The base pretrain model is megagonlabs/transformers-ud-japanese-electra-base-discrimininator.

The entire spaCy v3 model is distributed as a python package named 'ja_ginza_electra' from PyPI along with 'GiNZA v5' which provides some custom pipeline components to recognize the Japanese bunsetu-phrase structures.
Try running it as below:## Licenses

The models are distributed under the terms of the MIT License.## Acknowledgments

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.

s
- mC4

Contains information from 'mC4' which is made available under the ODC Attribution License.


- UD\_Japanese\_BCCWJ r2.8



- GSK2014-A(2019)