Instructions to use Nextcloud-AI/opus-mt-ja-sv with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Nextcloud-AI/opus-mt-ja-sv 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="Nextcloud-AI/opus-mt-ja-sv")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Nextcloud-AI/opus-mt-ja-sv") model = AutoModelForSeq2SeqLM.from_pretrained("Nextcloud-AI/opus-mt-ja-sv") - Notebooks
- Google Colab
- Kaggle
| tags: | |
| - translation | |
| license: apache-2.0 | |
| ### opus-mt-ja-sv | |
| * source languages: ja | |
| * target languages: sv | |
| * OPUS readme: [ja-sv](https://github.com/Helsinki-NLP/OPUS-MT-train/blob/master/models/ja-sv/README.md) | |
| * dataset: opus | |
| * model: transformer-align | |
| * pre-processing: normalization + SentencePiece | |
| * download original weights: [opus-2020-01-09.zip](https://object.pouta.csc.fi/OPUS-MT-models/ja-sv/opus-2020-01-09.zip) | |
| * test set translations: [opus-2020-01-09.test.txt](https://object.pouta.csc.fi/OPUS-MT-models/ja-sv/opus-2020-01-09.test.txt) | |
| * test set scores: [opus-2020-01-09.eval.txt](https://object.pouta.csc.fi/OPUS-MT-models/ja-sv/opus-2020-01-09.eval.txt) | |
| ## Benchmarks | |
| | testset | BLEU | chr-F | | |
| |-----------------------|-------|-------| | |
| | Tatoeba.ja.sv | 26.1 | 0.445 | | |