Instructions to use Helsinki-NLP/opus-mt-ja-en with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Helsinki-NLP/opus-mt-ja-en with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "translation" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # 'pip install "transformers<5.0.0' from transformers import pipeline pipe = pipeline("translation", model="Helsinki-NLP/opus-mt-ja-en")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Helsinki-NLP/opus-mt-ja-en") model = AutoModelForSeq2SeqLM.from_pretrained("Helsinki-NLP/opus-mt-ja-en", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
| tags: | |
| - translation | |
| ### opus-mt-ja-en | |
| * source languages: ja | |
| * target languages: en | |
| * OPUS readme: [ja-en](https://github.com/Helsinki-NLP/OPUS-MT-train/blob/master/models/ja-en/README.md) | |
| * dataset: opus | |
| * model: transformer-align | |
| * pre-processing: normalization + SentencePiece | |
| * download original weights: [opus-2019-12-18.zip](https://object.pouta.csc.fi/OPUS-MT-models/ja-en/opus-2019-12-18.zip) | |
| * test set translations: [opus-2019-12-18.test.txt](https://object.pouta.csc.fi/OPUS-MT-models/ja-en/opus-2019-12-18.test.txt) | |
| * test set scores: [opus-2019-12-18.eval.txt](https://object.pouta.csc.fi/OPUS-MT-models/ja-en/opus-2019-12-18.eval.txt) | |
| ## Benchmarks | |
| | testset | BLEU | chr-F | | |
| |-----------------------|-------|-------| | |
| | Tatoeba.ja.en | 41.7 | 0.589 | | |