Datasets:

procesaur
/

STARS

	---
	language:
	- sr
	pretty_name: S.T.A.R.S.
	size_categories:
	- 100M<n<1B
	configs:
	- config_name: default
	data_files:
	- split: train
	path:
	- '*_sr.jsonl'
	- '*cnr_.jsonl'
	task_categories:
	- text-generation
	license: cc-by-sa-4.0
	---

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


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

	<td colspan=2 align=center>
	<h1>S.T.A.R.S.</h1>
	</td>
	<tr-->
	<tr style="width:100%;height:100%">
	<td width=50%>
	<h2>Скуп Теза и Академских Радова на Српском</h2>
	<p><span class="highlight-container"><span class="highlight">Високо-квалитетан скуп</span></span> објављених научних радова писаних на српском језику.</p>
	<p>Неопходан за обучавање квалитетних језичких модела за српски језик.</p>
	<p>Укупно 24,165 докумената, укупно са 29 милиона реченица и<span class="highlight-container"><span class="highlight">преко 700 милиона речи</span></span>.</p>
	<p>Филтрирање могуће по институцијама, ауторима, кључним речима.</p>
	<p>Свака ЈСОН линија представља једну публикацију.</p>
	<p>Унутар сваког документа су обележене реченице и параграфи.</p>
	</td>
	<td>
	<h2>Set of Thesis and Academic Research in Serbian</h2>
	<p><span class
	="highlight-container"><span class="highlight">Highly curated, High-quality</span></span>, Serbian scientific corpus</p>
	<p>Necessary for training quality language models for Serbian.</p>
	<p>A total of 24,165 documents containing 29 million sentences and<span class="highlight-container"><span class="highlight">over 700 million words</span></span>.</p>
	<p>Filtering possible by institutions, authors, keywords.</p>
	<p>Each JSON line represents one publication.</p>
	<p>All documents are paragraph and sentence-delimited.</p>
	</td>
	</tr>
	<tr>
	<td>Izvori:</td>
	<td>Sources</td>
	</tr>
	<tr>
	<td colspan=2>
	<table style='width:100%;font-size:14pt;text-align:right'>
	<tr>
	<th style='width:40%'></th>
	<th style='width:15%'>Број докумената<br/>Doc. count</th>
	<th style='width:15%'>Број реченица<br/>Sent. count</th>
	<th style='width:15%'>Број речи<br/>Word count</th>
	<th style='width:15%'>Удео<br/>Share</th>
	</tr>
	<tr>
	<td>НАРДУС дисертације<br/>NARDUS doc. dissertations</td>
	<td>11,598</td>
	<td>23,471,447</td>
	<td>570,000,000</td>
	<td>80.3%</td>
	</tr>
	<tr>
	<td>Институционални репозиторијуми<br/>Institutional repositories</td>
	<td>12,174</td>
	<td>4,880,229</td>
	<td>123,000,000</td>
	<td>17.4%</td>
	</tr>
	<tr>
	<td>Универзитет Црне Горе<br/>University of Montenegro</td>
	<td>324</td>
	<td>630,025</td>
	<td>14,500,000</td>
	<td>2%</td>
	</tr>
	<tr>
	<td>OpenSlovenia</td>
	<td>61</td>
	<td>51,612</td>
	<td>1,265,000</td>
	<td>0.2%</td>
	</tr>
	<tr>
	<td>Универзитет у Источном Сарајеву<br/>University of East Sarajevo</td>
	<td>8</td>
	<td>24,153</td>
	<td>530,000</td>
	<td>0.1%</td>
	</tr>
	</table>
	</td>
	</tr>
	</table>



	```python
	from datasets import load_dataset
	dataset = load_dataset("procesaur/STARS")["train"]["text"]
	```


	```python
	print(dataset[0])
	'<s>Na oraničnim površinama gaje se raznovrsne ratarske kulture koje imaju važno mesto u našoj...'
	```


	<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: 14
	px;">@procesaur</div>
	</a>
	</div>
	</div>
	</div>

	<div class="inline-flex flex-col" style="line-height: 1.5;">

	<div style="text-align: center; margin-top: 3px; font-size: 16px; font-weight: 800">Editor</div>
	<a href="https://huggingface.co/Nikola-92">
	<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://aeiljuispo.cloudimg.io/v7/https://cdn-uploads.huggingface.co/production/uploads/656fa4e1b7b6010db395b74d/3W5VhwkSJ3JSGvlgsx2fx.jpeg?w=200&h=200&f=face)">
	</div>
	</div>
	</a>
	<div style="text-align: center; font-size: 16px; font-weight: 800">Nikola Janković</div>
	<div>
	<a href="https://huggingface.co/Nikola-92">
	<div style="text-align: center; font-size: 14px;">@Nikola-92</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},
	url = {https://arxiv.org/abs/2405.09250}
	}
	```

	<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>
	</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>

	<div id="zastava">
	<div class="grb">
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	</table>
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	<table style="width:100%;height:100%">
	<tr style="width:100%;height:100%">
	<td width=50%>
	<h4>За комплетне метаподатке докторских дисертација погледајте<a href="https://huggingface.co/datasets/jerteh/NARDUS-meta" class="highlight-container">
	<b class="highlight">NARDUS-meta</b></a> (метаподаци 13,289 дисертација са<a href="https://nardus.mpn.gov.rs/">НАРДУС-а</a>).</h4>
	<h4>За паралелни КОРПУС ПРЕВОДА сажетака погледајте<a href="https://huggingface.co/datasets/jerteh/PaSaz" class="highlight-container">
	<b class="highlight">PaSaž</b></a> (преко 20,000 паралелних сегмената).</h4>
	</td>
	<td>
	<h4>For the complete metadata check out <a href="https://huggingface.co/datasets/jerteh/NARDUS-meta" class="highlight-container">
	<b class="highlight">NARDUS-meta</b></a> (metadata for 13,289 dissertations from <a href="https://nardus.mpn.gov.rs/">NARDUS-a</a>).</h4>
	<h4>For the coprus of PARALEL TRANSALTIONS check out <a href="https://huggingface.co/datasets/jerteh/PaSaz" class="highlight-container">
	<b class="highlight">PaSaž</b></a> (over 20,000 paralel segments).</h4>
	</td>
	</tr>
	</table>

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