README.md

---
license: cc-by-4.0
datasets:
- procesaur/znanje
- procesaur/Vikipedija
- procesaur/Vikizvornik
- procesaur/kisobran
- jerteh/SrpELTeC
language:
- sr
---
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<td colspan=2>
  <h4><i class="highlight-container"><b class="highlight">PiloT5</b></i></h4>
</td>
</tr-->
  <tr style="width:100%;height:100%">
    <td width=50%>
      <p>Аутоенкодер заснован на Т5 архитектури - 248 милиона параметара</p>
      <p>Обучаван над корпусом српског језика - 4 милијарди речи</p>
      <!--p>Једнака подршка уноса на ћирилици и латиници!</p-->
    </td>
    <td>
      <p>T5 based Autoencoder - 248 million parameters</p>
      <p>Trained on Serbian corpora - 4 billion words</p>
      <!--p>Equal support for Cyrillic and Latin input!</p-->
    </td>
  </tr>
  </table>

```python
>>> from transformers import T5ForConditionalGeneration, T5TokenizerFast
>>> import torch

>>> model = T5ForConditionalGeneration.from_pretrained("te-sla/pilot5")
>>> tokenizer = T5TokenizerFast.from_pretrained("te-sla/pilot5")
>>> text = "ova sekcija sadrži ideje za prioritetne pravce/teme razvoja jezičkih tehnologija (NLP) za srpski jezik. Alternativni pravci razvoja su ukratko pobrojani u odeljku H2."
>>> input = tokenizer(text, return_tensors="pt")

>>> with torch.no_grad():
>>>     output = model.generate(input_ids=input["input_ids"], attention_mask=input["attention_mask"], do_sample=False, max_length=512)
>>> decoded_output = tokenizer.decode(output[0], skip_special_tokens=True)
>>> print(decoded_output)
```

```python
>>> ova sekcija sadrži ideje za prioritetne pravce/teme razvoja jezičkih tehnologija (NLP) za srpski jezik. Alternativni pravci razvoja su ukratko pobrojani u odeljku H2.
```


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<td width=50%>
  <h5><i><b>Евалуација на задатку сумаризације - српски језик</b></i></h4>
</td>
<td>
  <h5><i><b>Evaluation on the summarization task - Serbian language</b></i></h4>
</td>
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      <img src="res.png" class="cover" style="max-width:650px">
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<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">Author</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(&#39;https://cdn-uploads.huggingface.co/production/uploads/1673534533167-63bc254fb8c61b8aa496a39b.jpeg?w=200&h=200&f=face&#39;)">
          </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: 14px;">@procesaur</div>
      </a>
    </div>
  </div>
</div>



<div class="inline-flex flex-col" style="line-height: 1.5;padding-right:40px"> 
  <div style="text-align: center; margin-top: 3px; font-size: 16px; font-weight: 800">Computation</div>
    <a href="https://www.ai.gov.rs/">  
      <div class="flex">
          <div
  			style="display:DISPLAY_1; margin-left: auto; margin-right: auto; width: 92px; height:92px; border-radius: 50%; 
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  background-position: center;">
          </div>
      </div>
    </a>
    <div style="text-align: center; font-size: 16px; font-weight: 800" title="nVidia DGX-zasnovan sistem">Nacionalna AI platforma</div>
    <div>  
      <a href="https://www.ai.gov.rs/">
      	<div style="text-align: center; font-size: 14px;">ai.gov.rs</div>
      </a>
    </div>
  </div>
</div>


<!--div>
## Cit.

```bibtex
@inproceedings{skorict5,
  author    = {Mihailo Škorić},
  title     = {Pilot Text to Text Transfer Transformer Model for Serbian Language},
  booktitle   = {ARTIFICAL INTELLIGENCE CONFERENCE},
  year      = {2025},
  address = {Belgrade}
  publisher = {SASA, Belgrade},
  url       = {}
}
```
</div-->
<br/>

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       <p>Истраживање jе спроведено уз подршку Фонда за науку Републике Србиjе, #7276, Text Embeddings – Serbian Language Applications – TESLA</p>
    </td>
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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</p>
    </td>
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