SAVRN
Search Contact SAVRN

Open-weight model · Translation

opus-mt-fi-en

by Helsinki-NLP Research Group Helsinki-NLP/opus-mt-fi-en

hfname: fin-eng - sourcelanguages: fin - targetlanguages: eng - opusreadmeurl: https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/fin-eng/README.md - originalrepo: Tatoeba-Challenge - srcconstituents: {'fin'} - tgtconstituents: {'eng'} …

Parameters
Context512
Weights602.7 MB
Licenseapache-2.0
AccessOpen weights
Monthly Downloads46k

Model Card

By Helsinki-NLP Research Group, published under apache-2.0, revision c4d8fff0f8f0.

hfname: fin-eng - sourcelanguages: fin - targetlanguages: eng - opusreadmeurl: https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/fin-eng/README.md - originalrepo: Tatoeba-Challenge - srcconstituents: {'fin'} - tgtconstituents: {'eng'} - srcmultilingual: False - tgtmultilingual: False - urlmodel: https://object.pouta.csc.fi/Tatoeba-MT-models/fin-eng/opus-2020-08-05.zip - urltestset: https://object.pouta.csc.fi/Tatoeba-MT-models/fin-eng/opus-2020-08-05.test.txt - srcalpha3: fin - tgtalpha3: eng - shortpair: fi-en - chrF2score: 0.6970000000000001 - brevitypenalty: 0.99 - reflen: 74651.0 - srcname: Finnish - tgtname: English - traindate: 2020-08-05 - srcalpha2: fi…

Read Helsinki-NLP Research Group's full model card

fin-eng

Benchmarks

testset BLEU chr-F
newsdev2015-enfi-fineng.fin.eng 25.3 0.536
newstest2015-enfi-fineng.fin.eng 26.9 0.547
newstest2016-enfi-fineng.fin.eng 29.0 0.571
newstest2017-enfi-fineng.fin.eng 32.3 0.594
newstest2018-enfi-fineng.fin.eng 23.8 0.517
newstest2019-fien-fineng.fin.eng 29.0 0.565
newstestB2016-enfi-fineng.fin.eng 24.5 0.527
newstestB2017-enfi-fineng.fin.eng 27.4 0.557
newstestB2017-fien-fineng.fin.eng 27.4 0.557
Tatoeba-test.fin.eng 53.4 0.697

System Info:

  • hf_name: fin-eng

  • source_languages: fin

  • target_languages: eng

  • opus_readme_url: https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/fin-eng/README.md

  • original_repo: Tatoeba-Challenge

  • tags: ['translation']

  • languages: ['fi', 'en']

  • src_constituents: {'fin'}

  • tgt_constituents: {'eng'}

  • src_multilingual: False

  • tgt_multilingual: False

  • prepro: normalization + SentencePiece (spm32k,spm32k)

  • url_model: https://object.pouta.csc.fi/Tatoeba-MT-models/fin-eng/opus-2020-08-05.zip

  • url_test_set: https://object.pouta.csc.fi/Tatoeba-MT-models/fin-eng/opus-2020-08-05.test.txt

  • src_alpha3: fin

  • tgt_alpha3: eng

  • short_pair: fi-en

  • chrF2_score: 0.6970000000000001

  • bleu: 53.4

  • brevity_penalty: 0.99

  • ref_len: 74651.0

  • src_name: Finnish

  • tgt_name: English

  • train_date: 2020-08-05

  • src_alpha2: fi

  • tgt_alpha2: en

  • prefer_old: False

  • long_pair: fin-eng

  • helsinki_git_sha: 480fcbe0ee1bf4774bcbe6226ad9f58e63f6c535

  • transformers_git_sha: 2207e5d8cb224e954a7cba69fa4ac2309e9ff30b

  • port_machine: brutasse

  • port_time: 2020-08-21-14:41

Configuration

Architecture
MarianMTModel
Context length (tokens)
512
Layers
6
Vocabulary size
59,659
Model type
marian

Identity and Version

Repository
Helsinki-NLP/opus-mt-fi-en
Publisher
Helsinki-NLP Research Group
Task
Translation
Modality
Text
Library
transformers
Parameters
Not stated by the source
Languages
fi, en
Revision
c4d8fff0f8f00b637f0578666f35cdacef354778
First published
2022-03-02
Last updated
2023-08-16

Files and Weights

11 files, 605.7 MB in total. The weights are 2 files totalling 602.7 MB in bin, h5.

Weights2 files · 602.7 MB
Configuration3 files · 2.8 KB
Tokenizer2 files · 1.4 MB
Documentation1 file · 2.6 KB
Other2 files · 1.6 MB
Repository1 file · 345 B
Every file
FileTypeSizeSHA-256
pytorch_model.binWeights301.1 MB 33acd3582070
tf_model.h5Weights301.6 MB c23891876798
config.jsonConfiguration1.4 KB
generation_config.jsonConfiguration293 B
metadata.jsonConfiguration1.1 KB
README.mdDocumentation2.6 KB
source.spmOther831.9 KB
target.spmOther789.8 KB
.gitattributesRepository345 B
tokenizer_config.jsonTokenizer44 B
vocab.jsonTokenizer1.4 MB

License and Download

License
apache-2.0
Access
Open weights, no gate
Download size
602.7 MB
Download from Helsinki-NLP Research Group

Released by Helsinki-NLP Research Group through its official repository on Hugging Face. Read the license.

Memory Requirements

PrecisionWeights in memory
As published602.7 MB

Weights only, from the published parameter count; the key-value cache and runtime add to this.

Questions About opus-mt-fi-en

Can I use opus-mt-fi-en commercially?

Yes. opus-mt-fi-en 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.

What is opus-mt-fi-en's context length?

512 tokens, from the maximum position embeddings in its published configuration.

Similar Models

source languages: nl; target languages: en; OPUS readme: nl-en; dataset: opus; model: transformer-align; pre-processing: normalization + SentencePiece.

Open weights apache-2.0 512 tokens transformers

Model · Translation

nllb-200-distilled-600M

AI at Meta

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…

Open weights cc-by-nc-4.0 1,024 tokens transformers

source languages: en; target languages: ru; OPUS readme: en-ru; dataset: opus; model: transformer-align; pre-processing: normalization + SentencePiece.

Open weights apache-2.0 512 tokens transformers

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

Open weights cc-by-4.0 512 tokens transformers

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…

Open weights apache-2.0 512 tokens transformers

source languages: de; target languages: en; OPUS readme: de-en; dataset: opus; model: transformer-align; pre-processing: normalization + SentencePiece.

Open weights apache-2.0 512 tokens transformers