Model Card (#1)

- Model Card (ed0317f25efd4f02ddd14874740600b267cb3a76)


Co-authored-by: Ezi Ozoani <Ezi@users.noreply.huggingface.co>

README.md

@@ -6,18 +6,60 @@ license: apache-2.0
 
 ### opus-mt-ru-en
 
-* source languages: ru
-* target languages: en
-*  OPUS readme: [ru-en](https://github.com/Helsinki-NLP/OPUS-MT-train/blob/master/models/ru-en/README.md)
+## Table of Contents
+- [Model Details](#model-details)
+- [Uses](#uses)
+- [Risks, Limitations and Biases](#risks-limitations-and-biases)
+- [Training](#training)
+- [Evaluation](#evaluation)
+- [Citation Information](#citation-information)
+- [How to Get Started With the Model](#how-to-get-started-with-the-model)
+
+## Model Details
+**Model Description:**
+- **Developed by:** Language Technology Research Group at the University of Helsinki
+- **Model Type:** Transformer-align
+- **Language(s):**  
+  - Source Language: Russian
+  - Target Language: English
+- **License:** Apache-2.0
+- **Resources for more information:**
+  - [GitHub Repo](https://github.com/Helsinki-NLP/OPUS-MT-train)
+
+
+
+## Uses
+
+#### Direct Use
+
+This model can be used for translation and text-to-text generation.
+
+
+## Risks, Limitations and Biases
+
+**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)](https://aclanthology.org/2021.acl-long.330.pdf) and [Bender et al. (2021)](https://dl.acm.org/doi/pdf/10.1145/3442188.3445922)).
+
+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)
+
+## Training
+#### Training Data
+##### Preprocessing
+* Pre-processing: Normalization + SentencePiece
+* Dataset: [opus](https://github.com/Helsinki-NLP/Opus-MT)
+* Download original weights: [opus-2020-02-26.zip](https://object.pouta.csc.fi/OPUS-MT-models/ru-en/opus-2020-02-26.zip)
+
+* 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)
+
+
+## Evaluation
+
+#### Results
 
-*  dataset: opus
-* model: transformer-align
-* pre-processing: normalization + SentencePiece
-* download original weights: [opus-2020-02-26.zip](https://object.pouta.csc.fi/OPUS-MT-models/ru-en/opus-2020-02-26.zip)
-* 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)
 * 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)
 
-## Benchmarks
+#### Benchmarks
 
 | testset               | BLEU  | chr-F |
 |-----------------------|-------|-------|
@@ -31,3 +73,24 @@ license: apache-2.0
 | newstest2019-ruen.ru.en 	| 31.4 	| 0.576 |
 | Tatoeba.ru.en 	| 61.1 	| 0.736 |
 
+## Citation Information
+
+```bibtex
+@InProceedings{TiedemannThottingal:EAMT2020,
+  author = {J{\"o}rg Tiedemann and Santhosh Thottingal},
+  title = {{OPUS-MT} — {B}uilding open translation services for the {W}orld},
+  booktitle = {Proceedings of the 22nd Annual Conferenec of the European Association for Machine Translation (EAMT)},
+  year = {2020},
+  address = {Lisbon, Portugal}
+ }
+```
+
+## How to Get Started With the Model
+
+```python
+from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
+
+tokenizer = AutoTokenizer.from_pretrained("Helsinki-NLP/opus-mt-ru-en")
+
+model = AutoModelForSeq2SeqLM.from_pretrained("Helsinki-NLP/opus-mt-ru-en")
+```