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---
dataset_info:
pretty_name: Vyakaran
creators:
- Sanskrit Datasets
license: Apache-2.0
language:
- sa-Deva
size_categories: 100K<n<1M
task_categories:
- token-classification
- language-modeling
- text-generation
tags:
- sanskrit
- tokenization
- morphology
- classical-literature
---
# Vyakaran
**616 k blazing Sanskrit sentences—43 classics to supercharge your NLP**
`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.
---
## At a Glance
| Metric | Value |
| ------ | ----- |
| Rows (sentence–token pairs) | **616 082** |
| Unique sentences | 607 713 |
| Unique token strings | 604 319 |
| File size | 323 MB (UTF‑8 CSV) |
| Columns | `index` · `sanskrit` · `tokens` |
| Licence | Apache 2.0 |
---
## ✨ Dataset Summary
> *Because Sanskrit is precision disguised as poetry.*
> 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.
---
## Data Fields
| Column | Type | Description |
| ------ | ---- | ----------- |
| `index` | `int32` | 0‑based row identifier (primary key). |
| `sanskrit` | `string` | Original sentence in Devanāgarī, NFC‑normalised UTF‑8. |
| `tokens` | `string` | Whitespace‑separated morphological tokens generated by a rule‑based Pāṇinian splitter. |
---
## Quick Start
```python
from datasets import load_dataset
ds = load_dataset("snskrt/Vyakaran", split="train")
print(ds[0]["sanskrit"])
# नन्दति लोकः सुकृतैः ...
tokens = ds[0]["tokens"].split()
```
## Bibetext
```
@misc{sanskrit_datasets_2025,
author = {Sanskrit Datasets},
title = {Vyakaran (Revision ca374f9)},
year = {2025},
url = {https://huggingface.co/datasets/snskrt/Vyakaran},
doi = {10.57967/hf/6073},
publisher = {Hugging Face}
}
``` |