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README.md
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---
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language:
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- sr
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pretty_name: SMEĆE
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size_categories:
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- 1B<n<10B
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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: '*.boiler'
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task_categories:
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- text-generation
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- text-classification
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---
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<img src="cover.png" class="cover">
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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>SMEĆE</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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<h2>Skup teksta koji je obeležen kao smeće prilikom pripremanja drugih korpusa</h2>
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<p>preko 556 miliona reči</p>
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<p>Može se koristiti za obučavanje modela za klasifikaciju smeća :)</p>
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<h4>Za korpuse pravog teksta za srpski jezik pogledajte <a href="https://huggingface.co/datasets/procesaur/STARS" class="highlight-container">
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<b class="highlight">S.T.A.R.S</b></a> (13,289 disertacija sa <a href="https://nardus.mpn.gov.rs/">NARDUS-a</a>) ili
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<a href="https://huggingface.co/datasets/procesaur/kisobran" class="highlight-container">
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<b class="highlight">Kišobran veb korpus</b></a> (najveći korpus za srpski jezik).</h4>
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</td>
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<td>
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<h2>A set of text marked as garbage/boilerplate when preparing other corpora</h2>
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<p>over 556 million words</p>
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<p>Can be used to train boilerplate classification models :)</p>
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<h4>For real text corpora for Serbian see <a href="https://huggingface.co/datasets/procesaur/STARS" class="highlight-container">
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<b class="highlight">S.T.A.R.S</b></a> (13,289 dissertations from <a href="https://nardus.mpn.gov.rs/">NARDUS</a>) or
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<a href="https://huggingface.co/datasets/procesaur/kisobran" class="highlight-container">
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<b class="highlight">Umbrella web corp.</b></a> (largest corpus for the Serbian language).</h4>
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</td>
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</tr>
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</table>
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```python
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from datasets import load_dataset
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dataset = load_dataset("procesaur/SMECE")
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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">Editor</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: 14
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px;">@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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Citation:
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```bibtex
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@article{skoric24korpusi,
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author = {\vSkori\'c, Mihailo and Jankovi\'c, Nikola},
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title = {New Textual Corpora for Serbian Language Modeling},
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journal = {Infotheca},
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volume = {24},
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issue = {1},
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year = {2024},
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publisher = {Zajednica biblioteka univerziteta u Srbiji, Beograd},
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url = {https://arxiv.org/abs/2405.09250}
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}
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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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.cover {
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width: 100%;
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margin-bottom: 5pt
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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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.highlight-container {
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display: inline-block;
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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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.highlight-container{
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padding:5px 10px
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}
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.highlight-container:before {
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content: " ";
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display: block;
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height: 100%;
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width: 100%;
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margin-left: 0px;
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margin-right: 0px;
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position: absolute;
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background: #e80909;
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transform: rotate(2deg);
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top: -1px;
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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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div.grb, #zastava>table {
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position:absolute;
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top:0px;
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left: 0px;
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margin:0px
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}
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div.grb>img, #zastava>table{
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margin:0px
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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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p {
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font-size:14pt
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}
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</style>
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