Datasets:
Tasks:
Text Generation
Modalities:
Text
Formats:
text
Size:
10M - 100M
ArXiv:
Tags:
webdataset
License:
Update README.md
Browse files
README.md
CHANGED
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<tr style="width:100%;height:100%">
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<td width=50%>
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<h2><span class="highlight-container"><b class="highlight">Kišobran korpus</b></span> - krovni veb korpus srpskog i srpskohrvatskog jezika</h2>
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<p>Najveća agregacija veb korpusa do sada,
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<p>Ukupno x dokumenata, ukupno sa <span class="highlight-container"><span class="highlight">preko 18.5 milijardi reči</span></span>.</p>
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<p></p>
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<p>Svaka linija predstavlja novi dokument</p>
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<p>Rečenice unutar dokumenata su obeležene.</p>
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<h4>Sadrži obrađene i deduplikovane verzije sledećih korpusa:</h4>
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<ul>
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</ul>
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<p>Deduplikacija je izvršena pomoću alata <a href="http://corpus.tools/wiki/Onion">onion</a> korišćenjem pretrage 6-torki i pragom dedumplikacije 75%.</p>
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</td>
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<td>
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<h2><span class="highlight-container"><b class="highlight">Umbrella corp.</b></span> - umbrella web corpus of Serbian and Serbo-Croatian</h2>
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<p>The largest aggregation of web corpora so far,
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<p>A total of x documents containing <span class="highlight-container"><span class="highlight">over 18.5 billion words</span></span>.</p>
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<p></p>
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<p>Each line represents a document.</p>
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<p>Each Sentence in a document is delimited.</p>
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<h4>Contains processed and deduplicated versions of the following corpora:</h4>
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<ul>
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</ul>
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<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>
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</td>
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</tr>
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</table>
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Load complete dataset / Učitavanje kopletnog dataseta
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```python
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from datasets import load_dataset
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<table style="width:100%;height:100%">
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<tr style="width:100%;height:100%">
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<td width=50%>
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<p
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-
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</td>
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<td>
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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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<p>Computer resources necessary for the deduplication of the corpus were provided by the National Platform for Artificial Intelligence of Serbia.</p>
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</td>
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</tr>
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p {
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font-size:14pt
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}
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</style>
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<tr style="width:100%;height:100%">
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<td width=50%>
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<h2><span class="highlight-container"><b class="highlight">Kišobran korpus</b></span> - krovni veb korpus srpskog i srpskohrvatskog jezika</h2>
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+
<p>Najveća agregacija veb korpusa do sada, pogodna za obučavanje velikih jezičkih modela za srpski jezik.</p>
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<p>Ukupno x dokumenata, ukupno sa <span class="highlight-container"><span class="highlight">preko 18.5 milijardi reči</span></span>.</p>
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<p></p>
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<p>Svaka linija predstavlja novi dokument</p>
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32 |
<p>Rečenice unutar dokumenata su obeležene.</p>
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<h4>Sadrži obrađene i deduplikovane verzije sledećih korpusa:</h4>
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|
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</td>
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<td>
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<h2><span class="highlight-container"><b class="highlight">Umbrella corp.</b></span> - umbrella web corpus of Serbian and Serbo-Croatian</h2>
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+
<p>The largest aggregation of web corpora so far, suitable for training Serbian large language models.</p>
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<p>A total of x documents containing <span class="highlight-container"><span class="highlight">over 18.5 billion words</span></span>.</p>
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<p></p>
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<p>Each line represents a document.</p>
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<p>Each Sentence in a document is delimited.</p>
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+
<h4>Contains processed and deduplicated versions of the following corpora:</h4>
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</td>
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</tr>
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</table>
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<table class="lista">
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<tr>
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<td>Korpus<br/>Coprora</td>
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<td>Jezik<br/>Language</td>
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<td>Broj reči<br/>Word count</td>
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<td>Broj dokumenata<br/>Doc. count</td>
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<td>Udeo<br/>Share</td>
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</tr>
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<tr>
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<td><a href="https://huggingface.co/datasets/HPLT/hplt_monolingual_v1_2">HPLT_sr</a></td>
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<td>🇷🇸</td>
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<td>2.9 M</td>
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<td>2.5 B</td>
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<td>13.74%</td>
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</tr>
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<tr>
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<td><a href="https://www.clarin.si/repository/xmlui/handle/11356/1807">MaCoCu_sr</a></td>
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<td>🇷🇸</td>
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<td>6.7 M</td>
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<td>2.1 B</td>
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<td>11.54%</td>
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</tr>
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<tr>
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<td><a href="https://huggingface.co/datasets/allenai/c4">MC4_sr</a></td>
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<td>🇷🇸</td>
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<td>2.3 M</td>
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<td>782 M</td>
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<td>4.19%</td>
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</tr>
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<tr>
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<td><a href="https://huggingface.co/datasets/cc100">cc100_sr</a></td>
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<td>🇷🇸</td>
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<td>2.3 M</td>
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<td>659 M</td>
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<td>3.53%</td>
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</tr>
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<tr>
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<td><a href="https://www.clarin.si/repository/xmlui/handle/11356/1752">PDRS1.0</a></td>
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<td>🇷🇸</td>
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<td>400 K</td>
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<td>506 M</td>
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<td>2.71%</td>
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</tr>
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<tr>
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<td><a href="https://huggingface.co/datasets/jerteh/SrpKorNews">SrpKorNews</a></td>
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<td>🇷🇸</td>
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<td>35 K</td>
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<td>469 M</td>
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<td>2.51%</td>
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</tr>
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<tr>
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<td><a href="https://huggingface.co/datasets/oscar-corpus/OSCAR-2301">OSCAR_sr</a></td>
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<td>🇷🇸</td>
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<td>500 K</td>
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<td>410 M</td>
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<td>2.2%</td>
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</tr>
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<tr>
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<td><a href="https://www.clarin.si/repository/xmlui/handle/11356/1063">srWaC</a></td>
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<td>🇷🇸</td>
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<td>1.2 M</td>
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<td>307 M</td>
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<td>1.65%</td>
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</tr>
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<tr>
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<td><a href="https://www.clarin.si/repository/xmlui/handle/11356/1426">CLASSLA_sr</a></td>
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<td>🇷🇸</td>
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<td>1.3 M</td>
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<td>240 M</td>
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<td>1.29%</td>
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</tr>
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<tr>
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<td><a href="https://www.clarin.si/repository/xmlui/handle/11356/1809">MaCoCu_cnr</a></td>
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<td>🇷🇸/🇲🇪</td>
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<td>500 K</td>
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<td>152 M</td>
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<td>0.82%</td>
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</tr>
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<tr>
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<td><a href="https://www.clarin.si/repository/xmlui/handle/11356/1429">meWaC</a></td>
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<td>🇷🇸/🇲🇪</td>
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<td>200 K</td>
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<td>41 M</td>
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<td>0.22%</td>
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</tr>
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<tr>
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<td><a href="https://huggingface.co/datasets/cc100">cc100_hr</a></td>
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<td>🇭🇷</td>
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<td>13.3 M</td>
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<td>2.5 B</td>
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<td>13.73%</td>
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</tr>
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<tr>
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<td><a href="https://www.clarin.si/repository/xmlui/handle/11356/1806">MaCoCu_hr</a></td>
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<td>🇭🇷</td>
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<td>8 M</td>
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<td>2.3 B</td>
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<td>12.63%</td>
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</tr>
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<tr>
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<td><a href="https://huggingface.co/datasets/HPLT/hplt_monolingual_v1_2">HPLT_hr</a></td>
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<td>🇭🇷</td>
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<td>2.3 M</td>
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<td>1.8 B</td>
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<td>9.95%</td>
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</tr>
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<tr>
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<td><a href="https://huggingface.co/datasets/classla/xlm-r-bertic-data">hr_news</a></td>
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<td>🇭🇷</td>
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<td>4.1 M</td>
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<td>1.4 B</td>
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<td>7.65%</td>
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</tr>
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<tr>
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<td><a href="https://www.clarin.si/repository/xmlui/handle/11356/1064">hrWaC</a></td>
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<td>🇭🇷</td>
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<td>3.1 M</td>
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<td>935 M</td>
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<td>5.01%</td>
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</tr>
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<tr>
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<td><a href="https://www.clarin.si/repository/xmlui/handle/11356/1426">CLASSLA_hr</a></td>
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<td>🇭🇷</td>
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<td>1.2 M</td>
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<td>160 M</td>
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<td>0.86%</td>
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</tr>
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<tr>
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<td><a href="https://www.clarin.si/repository/xmlui/handle/11356/1180">riznica</a></td>
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<td>🇭🇷</td>
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<td>20 K</td>
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<td>69 M</td>
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<td>0.37%</td>
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</tr>
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<tr>
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<td><a href="https://www.clarin.si/repository/xmlui/handle/11356/1808">MaCoCu_bs</a></td>
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<td>🇧🇦</td>
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<td>2.6 M</td>
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<td>700 M</td>
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<td>3.75%</td>
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</tr>
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<tr>
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<td><a href="https://www.clarin.si/repository/xmlui/handle/11356/1062">bsWaC</a></td>
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<td>🇧🇦</td>
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<td>800 K</td>
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<td>194 M</td>
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<td>1.04%</td>
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</tr>
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<tr>
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<td><a href="https://www.clarin.si/repository/xmlui/handle/11356/1426">CLASSLA_bs</a></td>
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<td>🇧🇦</td>
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<td>800 K</td>
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<td>105 M</td>
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<td>0.56%</td>
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</tr>
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<tr>
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<td><a href="https://huggingface.co/datasets/cc100">cc100_bs</a></td>
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<td>🇧🇦</td>
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<td>300 K</td>
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<td>9 M</td>
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<td>0.05%</td>
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</tr>
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<tr>
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<td><a href="">TOTAL</a></td>
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<td></td>
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<td><b>54.75 M</b></td>
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<td><b>18.65 B</b></td>
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<td>100%</td>
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</tr>
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</table>
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Load complete dataset / Učitavanje kopletnog dataseta
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```python
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from datasets import load_dataset
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<table style="width:100%;height:100%">
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<tr style="width:100%;height:100%">
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<td width=50%>
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<p>Istraživanje je sprovedeno uz podršku Fonda za nauku Republike Srbije, #7276, Text Embeddings – Serbian Language Applications – TESLA.</p>
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<p>Svaki korpus u tabeli vezan je za URL sa kojeg je preuzet. Prikazani brojevi dokumenata i reči, odnose se na stanje nakon čićenja i deduplikacije.</p>
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<p>Deduplikacija je izvršena pomoću alata <a href="http://corpus.tools/wiki/Onion">onion</a> korišćenjem pretrage 6-torki i pragom dedumplikacije 75%.</p>
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<p>Računarske resursre neophodne za deduplikaciju korpusa obezbedila je Nacionalna platforma za veštačku inteligenciju Srbije.</p>
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</td>
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<td>
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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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<p>Each corpus in the table is linked to the URL from which it was downloaded. The displayed numbers of documents and words refer to after cleaning and deduplication.</p>
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<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>
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<p>Computer resources necessary for the deduplication of the corpus were provided by the National Platform for Artificial Intelligence of Serbia.</p>
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</td>
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</tr>
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p {
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font-size:14pt
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}
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.lista tr{
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line-height:1.2
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}
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</style>
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