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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'
---




<table style="width:100%;height:100%">
  <!--tr style="width:100%;height:30px">

  <td colspan=2 align=center>
    
  </td>
  <tr-->
  <tr style="width:100%;height:100%">
    <td width=50%>
      <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>
    </td>
    <td width=50%> 
      <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> 
    </td>
  </tr>
</tr>
  <tr>
    <td colspan=2>
      <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>
        </tr>
      </table>
    </td>
  </tr>   
    <tr>
    <td colspan=2>
      <table style='width:100%;font-size:12pt;text-align:right'>
        <tr>
           <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>
        </tr>
      </table>
    </td>
  </tr>   
</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">  
      <div class="flex">
          <div
  			style="display:DISPLAY_1; margin-left: auto; margin-right: auto; width: 92px; height:92px; border-radius: 50%; 
            background-size: cover; background-image: url(&#39;https://cdn-uploads.huggingface.co/production/uploads/1673534533167-63bc254fb8c61b8aa496a39b.jpeg?w=200&h=200&f=face&#39;)">
          </div>
      </div>
    </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>
    </div>
  </div>
</div>


<img src="cover.png" class="cover">


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    <img src="https://www.ai.gov.rs/img/logo_60x120-2.png" style="position:relative; left:30px; z-index:10; height:85px">
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<table style="width:100%;height:100%">
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    <td width=50%>
       <p>Истраживање jе спроведено уз подршку Фонда за науку Републике Србиjе, #7276, Text Embeddings – Serbian Language Applications – TESLA</p>
    </td>
    <td>
      <p>This research was supported by the Science Fund of the Republic of Serbia, #7276, Text Embeddings - Serbian Language Applications - TESLA</p>
    </td>
  </tr>
</table-->



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