source languages: nl; target languages: en; OPUS readme: nl-en; dataset: opus; model: transformer-align; pre-processing: normalization + SentencePiece.
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Open-weight model · Translation
by Helsinki-NLP Research Group Helsinki-NLP/opus-mt-eu-es
hfname: eus-spa - sourcelanguages: eus - targetlanguages: spa - opusreadmeurl: https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/eus-spa/README.md - originalrepo: Tatoeba-Challenge - srcconstituents: {'eus'} - tgtconstituents: {'spa'} …
By Helsinki-NLP Research Group, published under apache-2.0, revision a9973c01fe81.
hfname: eus-spa - sourcelanguages: eus - targetlanguages: spa - opusreadmeurl: https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/eus-spa/README.md - originalrepo: Tatoeba-Challenge - srcconstituents: {'eus'} - tgtconstituents: {'spa'} - srcmultilingual: False - tgtmultilingual: False - urlmodel: https://object.pouta.csc.fi/Tatoeba-MT-models/eus-spa/opus-2020-06-17.zip - urltestset: https://object.pouta.csc.fi/Tatoeba-MT-models/eus-spa/opus-2020-06-17.test.txt - srcalpha3: eus - tgtalpha3: spa - shortpair: eu-es - chrF2score: 0.6729999999999999 - brevitypenalty: 0.9640000000000001 - reflen: 12469.0 - srcname: Basque - tgtname: Spanish - traindate: 2020-06-17 - srcalpha2…
OPUS readme: eus-spa
model: transformer-align
| testset | BLEU | chr-F |
|---|---|---|
| Tatoeba-test.eus.spa | 48.8 | 0.673 |
hf_name: eus-spa
source_languages: eus
target_languages: spa
opus_readme_url: https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/eus-spa/README.md
original_repo: Tatoeba-Challenge
tags: ['translation']
languages: ['eu', 'es']
src_constituents: {'eus'}
tgt_constituents: {'spa'}
src_multilingual: False
tgt_multilingual: False
prepro: normalization + SentencePiece (spm32k,spm32k)
url_model: https://object.pouta.csc.fi/Tatoeba-MT-models/eus-spa/opus-2020-06-17.zip
url_test_set: https://object.pouta.csc.fi/Tatoeba-MT-models/eus-spa/opus-2020-06-17.test.txt
src_alpha3: eus
tgt_alpha3: spa
short_pair: eu-es
chrF2_score: 0.6729999999999999
bleu: 48.8
brevity_penalty: 0.9640000000000001
ref_len: 12469.0
src_name: Basque
tgt_name: Spanish
train_date: 2020-06-17
src_alpha2: eu
tgt_alpha2: es
prefer_old: False
long_pair: eus-spa
helsinki_git_sha: 480fcbe0ee1bf4774bcbe6226ad9f58e63f6c535
transformers_git_sha: 2207e5d8cb224e954a7cba69fa4ac2309e9ff30b
port_machine: brutasse
port_time: 2020-08-21-14:41
11 files, 599.2 MB in total. The weights are 2 files totalling 596.2 MB in bin, h5.
| File | Type | Size | SHA-256 |
|---|---|---|---|
| pytorch_model.bin | Weights | 297.8 MB | b55e6ab8ee02 |
| tf_model.h5 | Weights | 298.3 MB | 91253e5d3c3c |
| config.json | Configuration | 1.4 KB | — |
| generation_config.json | Configuration | 293 B | — |
| metadata.json | Configuration | 1.1 KB | — |
| README.md | Documentation | 2.1 KB | — |
| source.spm | Other | 825.4 KB | — |
| target.spm | Other | 834.4 KB | — |
| .gitattributes | Repository | 345 B | — |
| tokenizer_config.json | Tokenizer | 44 B | — |
| vocab.json | Tokenizer | 1.4 MB | — |
Released by Helsinki-NLP Research Group through its official repository on Hugging Face. Read the license.
| Precision | Weights in memory |
|---|---|
| As published | 596.2 MB |
Weights only, from the published parameter count; the key-value cache and runtime add to this.
Yes. opus-mt-eu-es 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.