en-ru-parallel-20m

20 million highest-quality English-Russian parallel sentence pairs.

Dataset Description

This dataset contains 20,000,000 carefully filtered English-Russian parallel sentence pairs. It was created specifically for machine translation, multilingual embedding training, model fine-tuning, and any other NLP tasks that require a large high-quality en-ru parallel corpus.

Dataset Summary

The corpus was built from ALL English-Russian datasets available on OPUS as of March 28, 2026.

A multi-stage cleaning and ranking pipeline was applied:

1. Heuristic filtering using the utilities from en-ru-corpus-utils.
2. Deduplication with removedup.
3. Quality ranking using LaBSE cosine similarity.
   To process the massive volume efficiently, LaBSE embeddings were computed via model2vec + PCA (pca_dims=300).
   Only the top 20 million pairs by similarity score were retained.

The dataset is sorted in descending order by LaBSE score (highest quality first).

Languages

• English (en)
• Russian (ru)

Data Fields

Column	Type	Description
english	string	English sentence
russian	string	Russian sentence
score	float32	LaBSE cosine similarity score (higher = better alignment). The dataset is sorted by this column in descending order.

Data Splits

Split	Number of examples
train	20,000,000

(No predefined validation or test splits — you can easily create them yourself.)

Usage

from datasets import load_dataset

dataset = load_dataset("KvaytG/en-ru-parallel-20m", split="train")

License & Legal Disclaimer

This dataset is an aggregation of multiple corpora sourced from the OPUS project.

Because it contains data from all available en-ru OPUS sources (as of March 28, 2026), it is a mixed-license collection. The underlying texts retain their original licenses, which vary significantly:

• Some data is Public Domain or permissive (e.g., Europarl, UNPC).
• Some data uses Copyleft licenses (e.g., CC-BY-SA for Wikipedia).
• Some data strictly prohibits commercial use (e.g., CC-BY-NC for TED/QED).
• Some data may be subject to copyright (e.g., OpenSubtitles).

Therefore, this aggregated dataset is not released under a single permissive license like MIT. By downloading and using this dataset, you acknowledge that:

1. The author of this dataset does not own the copyright to the underlying texts.
2. The dataset is provided primarily for research and educational purposes.
3. You are solely responsible for ensuring that your use of this data (especially in commercial applications) complies with the original licenses of the respective OPUS sub-corpora.

Citation

@misc{kvaytg_en_ru_parallel_20m,
  author       = {KvaytG},
  title        = {en-ru-parallel-20m: 20M high-quality English-Russian parallel corpus},
  year         = {2026},
  publisher    = {Hugging Face},
  url          = {https://huggingface.co/datasets/KvaytG/en-ru-parallel-20m},
  note         = {Built from all OPUS en-ru corpora (28 Mar 2026) with heuristic cleaning, deduplication and LaBSE ranking via model2vec+PCA}
}