Model Card
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Ezi
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README.md
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### opus-mt-ru-en
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* test set scores: [opus-2020-02-26.eval.txt](https://object.pouta.csc.fi/OPUS-MT-models/ru-en/opus-2020-02-26.eval.txt)
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| testset | BLEU | chr-F |
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|-----------------------|-------|-------|
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| newstest2019-ruen.ru.en | 31.4 | 0.576 |
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| Tatoeba.ru.en | 61.1 | 0.736 |
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### opus-mt-ru-en
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## Table of Contents
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- [Model Details](#model-details)
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- [Uses](#uses)
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- [Risks, Limitations and Biases](#risks-limitations-and-biases)
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- [Training](#training)
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- [Evaluation](#evaluation)
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- [Citation Information](#citation-information)
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- [How to Get Started With the Model](#how-to-get-started-with-the-model)
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## Model Details
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**Model Description:**
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- **Developed by:** Language Technology Research Group at the University of Helsinki
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- **Model Type:** Transformer-align
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- **Language(s):**
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- Source Language: Russian
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- Target Language: English
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- **License:** Apache-2.0
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- **Resources for more information:**
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- [GitHub Repo](https://github.com/Helsinki-NLP/OPUS-MT-train)
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## Uses
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#### Direct Use
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This model can be used for translation and text-to-text generation.
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## Risks, Limitations and Biases
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**CONTENT WARNING: Readers should be aware this section contains content that is disturbing, offensive, and can propagate historical and current stereotypes.**
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Significant research has explored bias and fairness issues with language models (see, e.g., [Sheng et al. (2021)](https://aclanthology.org/2021.acl-long.330.pdf) and [Bender et al. (2021)](https://dl.acm.org/doi/pdf/10.1145/3442188.3445922)).
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Further details about the dataset for this model can be found in the OPUS readme: [ru-en](https://github.com/Helsinki-NLP/OPUS-MT-train/blob/master/models/ru-en/README.md)
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## Training
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#### Training Data
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##### Preprocessing
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* Pre-processing: Normalization + SentencePiece
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* Dataset: [opus](https://github.com/Helsinki-NLP/Opus-MT)
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* Download original weights: [opus-2020-02-26.zip](https://object.pouta.csc.fi/OPUS-MT-models/ru-en/opus-2020-02-26.zip)
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* Test set translations: [opus-2020-02-26.test.txt](https://object.pouta.csc.fi/OPUS-MT-models/ru-en/opus-2020-02-26.test.txt)
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## Evaluation
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#### Results
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* test set scores: [opus-2020-02-26.eval.txt](https://object.pouta.csc.fi/OPUS-MT-models/ru-en/opus-2020-02-26.eval.txt)
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#### Benchmarks
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| testset | BLEU | chr-F |
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|-----------------------|-------|-------|
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| newstest2019-ruen.ru.en | 31.4 | 0.576 |
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| Tatoeba.ru.en | 61.1 | 0.736 |
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## Citation Information
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```bibtex
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@InProceedings{TiedemannThottingal:EAMT2020,
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author = {J{\"o}rg Tiedemann and Santhosh Thottingal},
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title = {{OPUS-MT} — {B}uilding open translation services for the {W}orld},
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booktitle = {Proceedings of the 22nd Annual Conferenec of the European Association for Machine Translation (EAMT)},
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year = {2020},
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address = {Lisbon, Portugal}
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}
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```
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## How to Get Started With the Model
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```python
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from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
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tokenizer = AutoTokenizer.from_pretrained("Helsinki-NLP/opus-mt-ru-en")
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model = AutoModelForSeq2SeqLM.from_pretrained("Helsinki-NLP/opus-mt-ru-en")
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```
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