five

BorisTM/bak-rus-parallel

收藏
Hugging Face2026-01-12 更新2026-03-29 收录
下载链接:
https://hf-mirror.com/datasets/BorisTM/bak-rus-parallel
下载链接
链接失效反馈
官方服务:
资源简介:
--- dataset_info: features: - name: bak dtype: string - name: rus dtype: string - name: static_sim dtype: float32 - name: source dtype: string - name: length_bak dtype: int64 - name: length_rus dtype: int64 splits: - name: train num_bytes: 3839636684 num_examples: 9768889 download_size: 1915872020 dataset_size: 3839636684 configs: - config_name: default data_files: - split: train path: data/train-* task_categories: - translation language: - ru - ba size_categories: - 1M<n<10M --- # Russian-Bashkir Parallel Corpus A large-scale parallel corpus for Russian-Bashkir machine translation, containing 9.7M sentence pairs filtered by semantic similarity. ## Dataset Details - **Languages**: Russian (`rus`) ↔ Bashkir (`bak`) - **Size**: 9,768,889 translation pairs - **Repository**: [`BorisTM/bak-rus-parallel`](https://huggingface.co/datasets/BorisTM/bak-rus-parallel) ## Usage ```python from datasets import load_dataset dataset = load_dataset("BorisTM/bak-rus-parallel") ``` ## Dataset Fields | Field | Type | Description | |-------|------|-------------| | `rus` | string | Russian sentence | | `bak` | string | Bashkir sentence | | `static_sim` | float32 | Semantic similarity score (cosine similarity, 0-1) | | `source` | string | Data source: `"real"` or `"synth"` | | `length_rus` | int64 | Character length of Russian sentence | | `length_bak` | int64 | Character length of Bashkir sentence | ## Dataset Composition The corpus combines two sources: ### Real Data (`source="real"`) Authentic human-created translations from the following parallel corpora: | Source | Description | |--------|-------------| | [`AigizK/bashkir-russian-parallel-corpora`](https://huggingface.co/datasets/AigizK/bashkir-russian-parallel-corpora) | Bashkir-Russian parallel corpus | | **TIL-MT Corpus** | Turkic Interlingua parallel corpus (ba-ru) | | **NLLB** (OPUS) | NLLB ba-ru parallel corpus from [opus.nlpl.eu](https://opus.nlpl.eu) | | **Wikimedia** (OPUS) | Wikimedia ba-ru parallel corpus from [opus.nlpl.eu](https://opus.nlpl.eu) | ### Synthetic Data (`source="synth"`) Generated via back-translation using the [`facebook/nllb-200-distilled-600M`](https://huggingface.co/facebook/nllb-200-distilled-600M) model on the following raw Bashkir text corpora: | Source | Description | |--------|-------------| | [`omarkamali/wikipedia-monthly`](https://huggingface.co/datasets/omarkamali/wikipedia-monthly) | Bashkir Wikipedia (2025-10-01 dump) | | [`HuggingFaceFW/fineweb-2`](https://huggingface.co/datasets/HuggingFaceFW/fineweb-2) | FineWeb-2 bak_Cyrl split | | [`cis-lmu/Glot500`](https://huggingface.co/datasets/cis-lmu/Glot500) | Glot500 bak_Cyrl split | | **HPOLT 3.0** | High-quality multilingual web text (bak_Cyrl) | ## Filtering All sentence pairs are filtered by the following criteria: - **Semantic similarity** > 0.25 (computed using [`BorisTM/static_rus_bak`](https://huggingface.co/BorisTM/static_rus_bak) embeddings) - **Sentence length**: <512 for both languages ## Statistics | Source | Count | |--------|-------| | Real | ~3.0M pairs | | Synthetic | ~6.8M pairs | | **Total** | **9.7M pairs** | ## License Please refer to the original source licenses for specific data components. ## Citation If you use this dataset, please cite: ```bibtex @dataset{bak_rus_parallel, title = {Russian-Bashkir Parallel Corpus}, author = {BorisTM}, year = {2025}, url = {https://huggingface.co/datasets/BorisTM/bak-rus-parallel} } ```
提供机构:
BorisTM
5,000+
优质数据集
54 个
任务类型
进入经典数据集
二维码
社区交流群

面向社区/商业的数据集话题

二维码
科研交流群

面向高校/科研机构的开源数据集话题

数据驱动未来

携手共赢发展

商业合作