---
license: cc-by-sa-4.0
task_categories:
- text-generation
language:
- sr
- hr
- bs
tags:
- webdataset
pretty_name: Umbrella corp.
size_categories:
- 10B<n<100B
---

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


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    <h1>Kišobran (Umbrella corp.)</h1>
  </td>
  <tr-->
  <tr style="width:100%;height:100%">
    <td width=50%>
      <h2><span class="highlight-container"><b class="highlight">Kišobran korpus</b></span> - krovni veb korpus srpskog i srpskohrvatskog jezika</h2>
      <p>Najveća agregacija veb korpusa do sada, neophodna za obučavanje velikih jezičkih modela za srpski jezik.</p>
      <p>Ukupno x dokumenata, ukupno sa <span class="highlight-container"><span class="highlight">preko 18.5 milijardi reči</span></span>.</p>
      <p></p>
      <p>Svaka linija predstavlja novi dokument</p>
      <p>Rečenice unutar dokumenata su obeležene.</p>    
      <h4>Sadrži obrađene i deduplikovane verzije sledećih korpusa:</h4>
      <ul>
      </ul>
       <p>Deduplikacija je izvršena pomoću alata <a href="http://corpus.tools/wiki/Onion">onion</a> korišćenjem pretrage 6-torki i pragom dedumplikacije 75%.</p>
    </td>
    <td>
      <h2><span class="highlight-container"><b class="highlight">Umbrella corp.</b></span> - umbrella web corpus of Serbian and Serbo-Croatian</h2>
      <p>The largest aggregation of web corpora so far, necessary for training Serbian large language models.</p>
      <p>A total of x documents containing <span class="highlight-container"><span class="highlight">over 18.5 billion words</span></span>.</p>
      <p></p>
      <p>Each line represents a document.</p>
      <p>Each Sentence in a document is delimited.</p>
      <h4>Contains processed and deduplicated versions of the following corpora:</h4>
      <ul>
      </ul>
      <p>The dataset was deduplicated using <a href="http://corpus.tools/wiki/Onion">onion</a> using 6-tuples search and a duplicate threshold of 75%.</p>
    </td>
  </tr>
</table>


Load complete dataset / Učitavanje kopletnog dataseta
```python
from datasets import load_dataset
dataset = load_dataset("procesaur/umbrella")
```


Load a specific language / Učitavanje pojedinačnih jezika
```python
from datasets import load_dataset
dataset_sr = load_dataset("procesaur/umbrella", "sr")
dataset_cnr = load_dataset("procesaur/umbrella", "cnr")
dataset_hr = load_dataset("procesaur/umbrella", "hr")
dataset_bs = load_dataset("procesaur/umbrella", "bs")
```


<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>
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Citation:
```bibtex
@article{skoric24korpusi,
  author    = {\vSkori\'c, Mihailo and Jankovi\'c, Nikola},
  title     = {New Textual Corpora for Serbian Language Modeling},
  journal   = {Infotheca},
  volume    = {24},
  issue     = {1},
  year      = {2024},
  publisher = {Zajednica biblioteka univerziteta u Srbiji, Beograd}
}
```


<table style="width:100%;height:100%">
  <tr style="width:100%;height:100%">
    <td width=50%>
       <p>Истраживање jе спроведено уз подршку Фонда за науку Републике Србиjе, #7276, Text Embeddings – Serbian Language Applications – TESLA.</p>
     <p>Računarske resursre neophodne za deduplikaciju korpusa obezbedila je Nacionalna platforma za veštačku inteligenciju Srbije.</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>
      <p>Computer resources necessary for the deduplication of the corpus were provided by the National Platform for Artificial Intelligence of Serbia.</p>
    </td>
  </tr>
</table>



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