WikiVarna / README.md
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---
license: cc-by-sa-3.0
task_categories:
- text-generation
language:
- bg
pretty_name: Viki Varna
size_categories:
- 100M<n<1B
configs:
- config_name: default
data_files:
- split: train
path:
- '*.jsonl'
- split: wikipedia
path:
- '*_wiki_*.jsonl'
- split: wikisource
path:
- '*_wikisource_*.jsonl'
- split: wikibooks
path:
- '*_wikibooks_*.jsonl'
- split: wikiquote
path:
- '*_wikiquote_*.jsonl'
- split: wikinews
path:
- '*_wikinews_*.jsonl'
---
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<h2>Уики корпуси на македонски и български език</h2>
<p>Нова версия, <span class="highlight-container"><span class="highlight">1 май 2026 г</span></span>!</p>
<p>Почистен и филтриран набор от пет проекта: Уикипедия, Уикиизточник, Уикикниги, Уикиновини и Уикицитат.</p>
<p>Над 240 000 курирани статии, с <span class="highlight-container"><span class="highlight">над 100 милиона думи.</span></span></p>
<p></p>
<p>Всеки документ е на отделен JSON ред.</p>
<p>Нови метаданни! Категории, брой думи и процент на кирилица</p>
<p>Възможно е да филтрирате набора по език или проект.</p>
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<h2>Wiki corpora in Bulgarian</h2>
<p>Fresh version, <span class="highlight-container"><span class="highlight">1. May 2026</span></span>!</p>
<p>Cleaned and filtered set of five projects: Wikipedia, Wikisource, Wikibooks, Wikinews and Wikiquotes.</p>
<p>Over 240,000 curated articles, with <span class="highlight-container"><span class="highlight">over 100 million words</span></span>.</p>
<p></p>
<p>Each document is in a separate JSON line.</p>
<p>New metadata! Categories, number of words and percentage of Cyrillic text</p>
<p>Possible to filter the set by language or project.</p>
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<table style='width:100%;font-size:12pt;text-align:right'>
<tr>
<th style='width:22%'><b>Брой документи<br/>Doc. count</b></th>
<th style='width:13%'><b>Уикипедия<br/>Wikipedia</b></th>
<th style='width:13%'><b>Уикиизточник<br/>Wikisource</b></th>
<th style='width:13%'><b>Уикиновини<br/>Wikinews</b></th>
<th style='width:13%'><b>Уикицитати<br/>Wikiquotes</b></th>
<th style='width:13%'><b>Уикикниги<br/>Wikibooks</b></th>
<th style='width:13%'><b>Общо<br/>Total</b></th>
</tr>
<tr>
<td>Български 🇧🇬</td>
<td>245,445</td>
<td>2,271</td>
<td>425</td>
<td>36</td>
<td>553</td>
<td>248,710</td>
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<th style='width:22%'><b>Брой думи<br/>Word count</b></th>
<th style='width:13%'><b>Уикипедия<br/>Wikipedia</b></th>
<th style='width:13%'><b>Уикиизточник<br/>Wikisource</b></th>
<th style='width:13%'><b>Уикиновини<br/>Wikinews</b></th>
<th style='width:13%'><b>Уикицитати<br/>Wikiquotes</b></th>
<th style='width:13%'><b>Уикикниги<br/>Wikibooks</b></th>
<th style='width:13%'><b>Общо<br/>Total</b></th>
</tr>
<tr>
<td>Български 🇧🇬</td>
<td>99,657,242</td>
<td>3,188,187</td>
<td>120,893</td>
<td>7,665</td>
<td>387,219</td>
<td>103,361,206</td>
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</table>
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</table>
```python
# Učitavanje samo vikicitata
dataset = load_dataset("procesaur/WikiVarna", split="wikiquote")
print(dataset[4]["text"])
```
```python
1 Цитати
* "Човекът е капка, течаща по мръсно стъкло. В началото капката е росна и бистра, като дестилирана вода...
```
```python
# Filtriranje prema metapodacima
filtered = dataset.filter(lambda example: example["subject"] == "Музиканти")
print(f"{filtered[0]["title"]}\n{filtered[0]["text"]} )
```
```python
Ники Минаж
Лил Уейн (Lil Wayne) ми е като баща – строг, поучаващ, загрижен. В началото на кариерата ми той често...
```
## Cite
```bibtex
@misc{škorić2026wikidumpstrainingcorpora,
title={Wiki Dumps to Training Corpora: South Slavic Case},
author={Mihailo Škorić},
year={2026},
eprint={2604.25384},
archivePrefix={arXiv},
primaryClass={cs.CL},
url={https://arxiv.org/abs/2604.25384},
}
```
<div class="inline-flex flex-col" style="line-height: 1.5;padding-right:50px">
<div style="text-align: center; margin-top: 3px; font-size: 16px; font-weight: 800">Editor</div>
<a href="https://huggingface.co/procesaur">
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<div
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</div>
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</a>
<div style="text-align: center; font-size: 16px; font-weight: 800">Mihailo Škorić</div>
<div>
<a href="https://huggingface.co/procesaur">
<div style="text-align: center; font-size: 14px;">@procesaur</div>
</a>
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<p>Истраживање jе спроведено уз подршку Фонда за науку Републике Србиjе, #7276, Text Embeddings – Serbian Language Applications – TESLA</p>
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<p>This research was supported by the Science Fund of the Republic of Serbia, #7276, Text Embeddings - Serbian Language Applications - TESLA</p>
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