Datasets:
Tasks:
Text Generation
Modalities:
Text
Formats:
text
Size:
100M - 1B
ArXiv:
Tags:
webdataset
License:
File size: 5,024 Bytes
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---
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">
<table style="width:100%;height:100%">
<!--tr style="width:100%;height:30px">
<td colspan=2 align=center>
<h1>Kišobran (Umbrella corp.)</h1>
</td>
<tr-->
<tr style="width:100%;height:100%">
<td width=50%>
<h2>Kišobran - 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 20 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>Umbrella corp. - 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 20 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('https://cdn-uploads.huggingface.co/production/uploads/1673534533167-63bc254fb8c61b8aa496a39b.jpeg?w=200&h=200&f=face')">
</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>
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}
}
```
<div id="zastava">
<div class="grb">
<img src="https://www.ai.gov.rs/img/logo_60x120-2.png" style="position:relative; left:30px; z-index:10; height:85px">
</div>
<table width=100% style="border:0px">
<tr style="background-color:#C6363C;width:100%;border:0px;height:30px"><td></td></tr>
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<tr style="background-color:#ffffff;width:100%;border:0px;height:30px"><td></td></tr>
</table>
</div>
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color:red
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font-size: 16pt;
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background: #e80909;
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p {
font-size:14pt
}
</style> |