source languages: nl; target languages: en; OPUS readme: nl-en; dataset: opus; model: transformer-align; pre-processing: normalization + SentencePiece.
Search public pages, research tools, and SAVRN solutions.
Open-weight model · Translation
by Helsinki-NLP Research Group Helsinki-NLP/opus-mt-en-fr
source languages: en; target languages: fr; OPUS readme: en-fr; dataset: opus; model: transformer-align; pre-processing: normalization + SentencePiece.
By Helsinki-NLP Research Group, published under apache-2.0, revision dd7f6540a7a4.
source languages: en; target languages: fr; OPUS readme: en-fr; dataset: opus; model: transformer-align; pre-processing: normalization + SentencePiece.
OPUS readme: en-fr
dataset: opus
| testset | BLEU | chr-F |
|---|---|---|
| newsdiscussdev2015-enfr.en.fr | 33.8 | 0.602 |
| newsdiscusstest2015-enfr.en.fr | 40.0 | 0.643 |
| newssyscomb2009.en.fr | 29.8 | 0.584 |
| news-test2008.en.fr | 27.5 | 0.554 |
| newstest2009.en.fr | 29.4 | 0.577 |
| newstest2010.en.fr | 32.7 | 0.596 |
| newstest2011.en.fr | 34.3 | 0.611 |
| newstest2012.en.fr | 31.8 | 0.592 |
| newstest2013.en.fr | 33.2 | 0.589 |
| Tatoeba.en.fr | 50.5 | 0.672 |
11 files, 903.7 MB in total. The weights are 3 files totalling 900.8 MB in bin, h5, msgpack.
| File | Type | Size | SHA-256 |
|---|---|---|---|
| flax_model.msgpack | Weights | 298.7 MB | 7b7ebb1b554e |
| pytorch_model.bin | Weights | 300.8 MB | cc1de10b4934 |
| tf_model.h5 | Weights | 301.3 MB | c860b5d50a25 |
| config.json | Configuration | 1.4 KB | — |
| generation_config.json | Configuration | 293 B | — |
| README.md | Documentation | 1.2 KB | — |
| source.spm | Other | 778.4 KB | — |
| target.spm | Other | 802.4 KB | — |
| .gitattributes | Repository | 391 B | — |
| tokenizer_config.json | Tokenizer | 42 B | — |
| vocab.json | Tokenizer | 1.3 MB | — |
Released by Helsinki-NLP Research Group through its official repository on Hugging Face. Read the license.
| Precision | Weights in memory |
|---|---|
| As published | 900.8 MB |
Weights only, from the published parameter count; the key-value cache and runtime add to this.
Yes. opus-mt-en-fr is released under Apache License 2.0. The Apache License 2.0 is a permissive open-source license. It permits commercial use, modification and redistribution. It requires keeping the license and copyright notices and any NOTICE file, stating significant changes, and it includes an express patent grant from contributors.
512 tokens, from the maximum position embeddings in its published configuration.
source languages: nl; target languages: en; OPUS readme: nl-en; dataset: opus; model: transformer-align; pre-processing: normalization + SentencePiece.
This is the model card of NLLB-200's distilled 600M variant. Here are the metrics for that particular checkpoint. - Information about training algorithms, parameters, fairness constraints or other applied approaches, and features. The exact training algorithm, data and the strategies to handle data imbalances for high and low resource languages that were used to train NLLB-200 is described in the paper. - Paper or other resource for more information NLLB Team et al, No Language Left Behind: Scaling Human-Centered Machine Translation, Arxiv, 2022 - Where to send questions or comments about the model: https://github.com/facebookresearch/fairseq/issues • Model performance measures: NLLB-200…
source languages: en; target languages: ru; OPUS readme: en-ru; dataset: opus; model: transformer-align; pre-processing: normalization + SentencePiece.
This model can be used for translation and text-to-text generation. CONTENT WARNING: Readers should be aware this section contains content that is disturbing, offensive, and can propagate historical and current stereotypes. Significant research has explored bias and fairness issues with language models (see, e.g., Sheng et al. (2021) and Bender et al. (2021)). Further details about the dataset for this model can be found in the OPUS readme: en-de
hfname: kor-eng - sourcelanguages: kor - targetlanguages: eng - opusreadmeurl: https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/kor-eng/README.md - originalrepo: Tatoeba-Challenge - srcconstituents: {'korHani', 'korHang', 'korLatn', 'kor'} - tgtconstituents: {'eng'} - srcmultilingual: False - tgtmultilingual: False - urlmodel: https://object.pouta.csc.fi/Tatoeba-MT-models/kor-eng/opus-2020-06-17.zip - urltestset: https://object.pouta.csc.fi/Tatoeba-MT-models/kor-eng/opus-2020-06-17.test.txt - srcalpha3: kor - tgtalpha3: eng - shortpair: ko-en - chrF2score: 0.588 - brevitypenalty: 0.9590000000000001 - reflen: 17711.0 - srcname: Korean - tgtname: English - traindate…
source languages: de; target languages: en; OPUS readme: de-en; dataset: opus; model: transformer-align; pre-processing: normalization + SentencePiece.