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  ### opus-mt-ru-en
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- * source languages: ru
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- * target languages: en
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- * OPUS readme: [ru-en](https://github.com/Helsinki-NLP/OPUS-MT-train/blob/master/models/ru-en/README.md)
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-
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- * dataset: opus
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- * model: transformer-align
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- * pre-processing: normalization + SentencePiece
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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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  * 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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  ### 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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+
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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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+
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+
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+
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+ ## Uses
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+
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+ #### Direct Use
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+
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+ This model can be used for translation and text-to-text generation.
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+
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+
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+ ## Risks, Limitations and Biases
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+
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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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+
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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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+
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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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+
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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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+
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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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+
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+
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+ ## Evaluation
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+
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+ #### Results
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+
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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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+
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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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+
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+ ## How to Get Started With the Model
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+
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+ ```python
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+ from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
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+
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+ tokenizer = AutoTokenizer.from_pretrained("Helsinki-NLP/opus-mt-ru-en")
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+
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+ model = AutoModelForSeq2SeqLM.from_pretrained("Helsinki-NLP/opus-mt-ru-en")
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+ ```