Vikipedija / README.md
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---
license: cc-by-sa-3.0
task_categories:
- text-generation
language:
- sr
pretty_name: Srpska Vikipedija
size_categories:
- 100M<n<1B
configs:
- config_name: default
data_files:
- split: train
path:
- wiki.sr.jsonl
---
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<h2>Srpska Vikipedija</h2>
<p>verzija 1.11.2023 - derivacija <a href="https://huggingface.co/datasets/wikimedia/wikipedia"><b>Vikimedijinog skupa</b></a></p>
<p>Ukupno 676,605 dokumenata, sa <span class="highlight-container"><span class="highlight">preko 135 miliona reči</span></span>.</p>
<p></p>
<p>Svaki dokument je u zasebnoj JSON liniji.</p>
<p>Paragrafi su odvojeni duplim novim redom (\n\n).</p>
<p>Rečenice unutar paragrafa su obeležene.</p>
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<h2>Serbian Wikipedia</h2>
<p>version 1.11.2023 - derived from <a href="https://huggingface.co/datasets/wikimedia/wikipedia"><b>Wikimedia dataset</b></a></p>
<p>A total of 676,60 documents containing <span class="highlight-container"><span class="highlight">over 135 million words</span></span>.</p>
<p></p>
<p>Each document is represented by a JSON line.</p>
<p>Paragraphs are separated via double new line (\n\n).</p>
<p>Each Sentence in a document is delimited.</p>
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```python
from datasets import load_dataset
dataset = load_dataset("procesaur/Vikipedija")
```
```python
print(dataset["train"][11])
{'text': '<s>Никола Тесла (Смиљан, 10. јул 1856 — Њујорк, 7. јануар 1943) био је српски...'}
```
<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">
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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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<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>
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<p>Истраживање jе спроведено уз подршку Фонда за науку Републике Србиjе, #7276, Text Embeddings – Serbian Language Applications – TESLA
и Фода за иновациону делатност Републике Србије у оквиру програма GOVTECH, решење #53096, Дигитекс</p>
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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
and the Fund for Republic of Serbia Innovation Fund via the GOVTECH program, project #53096, Digiteks</p>
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