FuguMT English-to-Japanese Translation Model
| Property | Value |
|---|---|
| License | CC-BY-SA-4.0 |
| Architecture | Marian-NMT |
| Framework | PyTorch, Transformers |
| BLEU Score | 32.7 (Tatoeba test set) |
What is fugumt-en-ja?
FuguMT is a specialized machine translation model designed for English to Japanese translation tasks. Built on the Marian-NMT architecture, it leverages modern transformer technology to provide accurate translations. With over 61,000 downloads and 51 likes, it has demonstrated its utility in the community.
Implementation Details
The model is implemented using the Transformers library and requires sentencepiece for tokenization. It can be easily integrated into Python applications and supports both single sentence and multi-sentence translation tasks through pySBD integration.
- Built with PyTorch and Transformers framework
- Uses sentencepiece tokenization
- Supports batch translation with pySBD sentence segmentation
- Evaluated on Tatoeba dataset with 500 randomly selected sentences
Core Capabilities
- Direct English to Japanese translation
- Sentence-level translation processing
- Integration with popular NLP pipelines
- Batch processing support
- 32.7 BLEU score with ja-mecab tokenization
Frequently Asked Questions
Q: What makes this model unique?
FuguMT stands out for its specialized focus on English-to-Japanese translation, achieving a competitive BLEU score of 32.7 on the Tatoeba test set. It's designed for easy integration with the Transformers pipeline, making it accessible for both developers and researchers.
Q: What are the recommended use cases?
The model is ideal for applications requiring English to Japanese translation, such as content localization, document translation, and NLP applications. It's particularly well-suited for scenarios requiring batch processing of multiple sentences, thanks to its pySBD integration.
