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--- |
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dataset_info: |
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pretty_name: Vyakaran |
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creators: |
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- Sanskrit Datasets |
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license: Apache-2.0 |
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language: |
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- sa-Deva |
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size_categories: 100K<n<1M |
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task_categories: |
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- token-classification |
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- language-modeling |
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- text-generation |
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tags: |
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- sanskrit |
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- tokenization |
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- morphology |
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- classical-literature |
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--- |
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# Vyakaran |
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**616 k blazing Sanskrit sentences—43 classics to supercharge your NLP** |
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`vyakaran.csv` distils two‑and‑a‑half millennia of Sanskrit wisdom into an analysis‑ready corpus: every line is a sentence from a public‑domain classic, paired with the whitespace‑separated tokens that emerge when you roll back *sandhi* and compounds. The result is a dependable springboard for tokenisers, morphological taggers, and large‑language‑model pre‑training. |
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--- |
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## At a Glance |
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| Metric | Value | |
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| ------ | ----- | |
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| Rows (sentence–token pairs) | **616 082** | |
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| Unique sentences | 607 713 | |
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| Unique token strings | 604 319 | |
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| File size | 323 MB (UTF‑8 CSV) | |
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| Columns | `index` · `sanskrit` · `tokens` | |
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| Licence | Apache 2.0 | |
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--- |
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## ✨ Dataset Summary |
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> *Because Sanskrit is precision disguised as poetry.* |
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> Vyakaran gathers verses, dialogue, and narrative from 43 classics—*Mahābhārata*, *Śiva Purāṇa*, *Tantrāloka*, *Buddha‑Carita*, and more—then hands you both the raw sentence and a token string you can feed straight to SentencePiece or a CRF tagger. Use it to **train segmenters, pre‑train transformers, benchmark morphology**, or just explore the linguistic art of the ancients. |
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--- |
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## Data Fields |
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| Column | Type | Description | |
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| ------ | ---- | ----------- | |
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| `index` | `int32` | 0‑based row identifier (primary key). | |
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| `sanskrit` | `string` | Original sentence in Devanāgarī, NFC‑normalised UTF‑8. | |
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| `tokens` | `string` | Whitespace‑separated morphological tokens generated by a rule‑based Pāṇinian splitter. | |
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--- |
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## Quick Start |
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```python |
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from datasets import load_dataset |
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ds = load_dataset("snskrt/Vyakaran", split="train") |
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print(ds[0]["sanskrit"]) |
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# नन्दति लोकः सुकृतैः ... |
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tokens = ds[0]["tokens"].split() |
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``` |
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## Bibetext |
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``` |
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@misc{sanskrit_datasets_2025, |
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author = {Sanskrit Datasets}, |
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title = {Vyakaran (Revision ca374f9)}, |
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year = {2025}, |
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url = {https://huggingface.co/datasets/snskrt/Vyakaran}, |
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doi = {10.57967/hf/6073}, |
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publisher = {Hugging Face} |
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} |
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``` |
