---
license: cc-by-nc-sa-4.0
language:
- sr
pretty_name: Sr Tokenizer test
configs:
- config_name: default
  data_files:
  - split: train
    path:
    - '*_train.jsonl'
  - split: test
    path:
    - '*_test.jsonl'
---

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# Sr Tokenizer test
This dataset provides a large Serbian text corpus designed for training and evaluating of tokenizers for Serbian language models. 
It combines multiple sources of Serbian text in both Cyrillic and Latin scripts, unified into a consistent JSONL format with id and text fields.

## Dataset Structure
Metadata has been stripped; Each record is a JSON object with:

- id: unique identifier
- text: raw Serbian text

## Source coprora

- [Znanje(sr) corpus](https://huggingface.co/datasets/procesaur/znanje): ~6.6 GB with 700 million words  
- [WikiViki(sr) corpus](https://huggingface.co/datasets/procesaur/WikiViki): ~1.5 GB with 135 million words
- [PDRS web corpus](http://hdl.handle.net/11356/1752): ~3.2 GB with 500 million words

total 11.3 GB with 1.3 billion words

#### Splits:
- train.jsonl (75%)
- test.jsonl (25%)

```python
from datasets import load_dataset
dataset = load_dataset("procesaur/sr-tokenizer-test", split="train")
```

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

```bibtex
soon
```


	
<!--table style="width:100%;height:100%">
ISLRN: 476-040-938-571-9
  <tr style="width:100%;height:100%">
    <td width=50%>
       <p>Istraživanje je sprovedeno uz podršku Fonda za nauku Republike Srbije, #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-->

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