Datasets:
| license: mit | |
| task_categories: | |
| - translation | |
| - token-classification | |
| language: | |
| - ur | |
| - en | |
| - zh | |
| - ar | |
| - hy | |
| - ak | |
| tags: | |
| - nmt | |
| - parallel-corpus | |
| - multilingual | |
| - urdu | |
| - large-scale | |
| - bitext | |
| - synthetic-data | |
| pretty_name: Vast Urdu Parallel Corpus | |
| # Vast Urdu Parallel Corpus | |
| ## Dataset Description | |
| **Vast-Urdu** is a large-scale collection of parallel text corpora specifically filtered to support Urdu (UR) language research. This dataset was extracted from the `liboaccn/nmt-parallel-corpus` to provide a dedicated resource for Neural Machine Translation (NMT), cross-lingual understanding, and token-classification tasks involving Urdu. | |
| ### Source Data | |
| The data is sourced from a massive web-scale crawl, containing sentence-aligned pairs between Urdu and several other languages including: | |
| * **English (en)** | |
| * **Chinese (zh)** | |
| * **Arabic (ar)** | |
| * **Armenian (hy)** | |
| * **Akan (ak)** | |
| ## Dataset Structure | |
| The files are provided in `.parquet` format for efficient storage and fast loading. Each file represents a language pair (e.g., `en-ur.parquet`), containing: | |
| - **Source text**: The text in the primary language. | |
| - **Target text**: The corresponding translation in Urdu (or vice-versa). | |
| ## Usage | |
| You can load this dataset directly using the Hugging Face `datasets` library: | |
| ```python | |
| from datasets import load_dataset | |
| dataset = load_dataset("ReySajju742/Vast-Urdu", data_files="en-ur.parquet") | |
| print(dataset['train'][0]) |