Datasets:
Tasks:
Text Generation
Modalities:
Text
Formats:
json
Languages:
Serbian
Size:
10K - 100K
ArXiv:
License:
Create README.md
Browse files
README.md
ADDED
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1 |
+
---
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2 |
+
language:
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- sr
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pretty_name: S.T.A.R.S.
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size_categories:
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- 100M<n<1B
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configs:
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- config_name: default
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data_files:
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- split: train
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path:
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- stars.txt
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task_categories:
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- text-generation
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---
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<img src="cover.png" class="cover">
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<div id="zastava">
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<div class="grb">
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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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</div>
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+
<table width=100% style="border:0px">
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<tr style="background-color:#C6363C;width:100%;border:0px;height:30px"><td></td></tr>
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<tr style="background-color:#0C4076;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>
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+
</table>
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</div>
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+
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<table style="width:100%;height:100%">
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<tr style="width:100%;height:30px">
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<td colspan=2 align=center>
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<h1>S.T.A.R.S.</h1>
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</td>
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<tr>
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<tr style="width:100%;height:100%">
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<td width=50%>
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<h3>Skup Teza i Akademskih Radova na Srpskom</h2>
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38 |
+
<p>Visoko-kvalitetan skup doktorskih disertacija objavljenih u Srbiji i pisanih na srpskom jeziku</p>
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39 |
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<p>Neophodan za obučavanje kvalitetnih jezičkih modela za srpski jezik.</p>
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<p>Ukupno 11,627 dokumenata, ukupno sa preko 600 miliona tokena.</p>
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<p></p>
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<p>Svaki dokument je odvojen duplom novom linijom.</p>
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<p>Svaka linija predstavlja jedan paragraf.</p>
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<p>Rečenice unutar paragrafa su obeležene.</p>
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</td>
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<td>
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<h3>Set of Thesis and Academic Research in Serbian</h2>
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<p>Highly curated, High-quality, Serbian doctoral dissertation corpus</p>
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<p>Necessary for training quality language models for Serbian.</p>
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<p>A total of 11,627 documents containing over 600 million tokens.</p>
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<p></p>
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<p>Each document is delimited with double newline.</p>
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<p>Each line represents paragraph.</p>
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<p>Each Sentence in a document is delimited.</p>
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55 |
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</td>
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</tr>
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</table>
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+
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+
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+
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```python
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from datasets import load_dataset
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dataset = load_dataset("procesaur/STARS")
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```
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```python
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print(dataset["train"][111])
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{'text': ''}
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```
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<div class="inline-flex flex-col" style="line-height: 1.5;padding-right:50px">
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<div style="text-align: center; margin-top: 3px; font-size: 16px; font-weight: 800">Autor</div>
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<a href="https://huggingface.co/procesaur">
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<div class="flex">
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<div
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style="display:DISPLAY_1; margin-left: auto; margin-right: auto; width: 92px; height:92px; border-radius: 50%;
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background-size: cover; background-image: url('https://cdn-uploads.huggingface.co/production/uploads/1673534533167-63bc254fb8c61b8aa496a39b.jpeg?w=200&h=200&f=face')">
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</div>
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</div>
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</a>
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<div style="text-align: center; font-size: 16px; font-weight: 800">Mihailo Škorić</div>
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<div>
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<a href="https://huggingface.co/procesaur">
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<div style="text-align: center; font-size: 14px;">@procesaur</div>
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</a>
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</div>
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</div>
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</div>
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<div class="inline-flex flex-col" style="line-height: 1.5;">
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|
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<div style="text-align: center; margin-top: 3px; font-size: 16px; font-weight: 800">Autor</div>
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<a href="https://huggingface.co/Nikola-92">
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<div class="flex">
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<div
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style="display:DISPLAY_1; margin-left: auto; margin-right: auto; width: 92px; height:92px; border-radius: 50%;
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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)">
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</div>
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</div>
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</a>
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<div style="text-align: center; font-size: 16px; font-weight: 800">Nikola Janković</div>
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<div>
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<a href="https://huggingface.co/Nikola-92">
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<div style="text-align: center; font-size: 14px;">@Nikola-92</div>
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</a>
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</div>
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</div>
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</div>
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Citation:
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```bibtex
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```
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<style>
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.ffeat: {
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color:red
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}
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+
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.cover {
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width: 100%;
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margin-bottom: 5pt
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}
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+
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.highlight-container, .highlight {
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position: relative;
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text-decoration:none
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}
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+
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.highlight-container {
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display: inline-block;
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+
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}
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+
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.highlight{
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color:white;
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text-transform:uppercase;
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font-size: 16pt;
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}
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+
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.highlight-container{
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padding:5px 10px
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}
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+
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+
.highlight-container:before {
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+
content: " ";
|
150 |
+
display: block;
|
151 |
+
height: 100%;
|
152 |
+
width: 100%;
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153 |
+
margin-left: 0px;
|
154 |
+
margin-right: 0px;
|
155 |
+
position: absolute;
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156 |
+
background: #e80909;
|
157 |
+
transform: rotate(2deg);
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158 |
+
top: -1px;
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159 |
+
left: -1px;
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+
border-radius: 20% 25% 20% 24%;
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+
padding: 10px 18px 18px 10px;
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+
}
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163 |
+
|
164 |
+
div.grb, #zastava>table {
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165 |
+
position:absolute;
|
166 |
+
top:0px;
|
167 |
+
left: 0px;
|
168 |
+
margin:0px
|
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+
}
|
170 |
+
|
171 |
+
div.grb>img, #zastava>table{
|
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+
margin:0px
|
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+
}
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+
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+
#zastava {
|
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+
position: relative;
|
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+
margin-bottom:120px
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+
}
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+
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+
p {
|
181 |
+
font-size:14pt
|
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+
}
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+
</style>
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