Model reference · open weights

transformers-ud-japanese-electra-ginza-510

Embeddings megagonlabs Embeddings 1 build Open weights 15k dl/mo

transformers-ud-japanese-electra-ginza-510 is an open-weight embedding model from megagonlabs. transformers-ud-japanese-electra-base-ginza-510 (BF16) weighs 434 MB; the smallest configuration that runs it is RTX 3060 12 GB.

For self-hosting, compare this build's requirements below with the GPU you plan to rent.

  • transformers-ud-japanese-electra-ginza-510 is a feature-extraction model developed by megagonlabs for Japanese language processing.
  • It is an ELECTRA architecture pretrained on approximately 200 million Japanese sentences from the mC4 dataset and fine-tuned on the UD_Japanese_BCCWJ r2.8 treebank.
  • The model supports a context length of 512 tokens and is distributed under the MIT license.

Summary of the megagonlabs/transformers-ud-japanese-electra-base-ginza-510 model card, 2026-10-01

What it is

Released bymegagonlabs
Released2022-03-02
VRAM434 MB for the weights

What it runs on

Memory and cards for transformers-ud-japanese-electra-base-ginza-510 (BF16)

434 MBweights, file size
1.1 GBruntime overhead
CardRunsMemory
RTX 3060 12 GBfits11.6 GB
RTX 4060 Ti 16 GBfits15.4 GB
RTX 3090 24 GBfits23.4 GB
RTX 4090 24 GBfits23.4 GB
RTX 5090 32 GBfits31.0 GB
L40S 48 GBfits44.0 GB
A100 80 GBfits78.2 GB
H100 80 GBfits78.1 GB
RTX PRO 6000 Blackwell 96 GBfits93.8 GB
DGX Spark (GB10) 128 GB unifiedfits107 GB
H200 141 GBfits138 GB
B200 180 GBfits176 GB

From the model card

What megagonlabs says about transformers-ud-japanese-electra-ginza-510

Read the model card

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:

$ pip install ginza ja_ginza_electra
$ ginza

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.

Citations

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

@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},
}
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.

Quoted from the model card on Hugging Face. The full card is behind the Hugging Face link above.

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