---
license: cc-by-sa-4.0
datasets:
- procesaur/Vikipedija
- procesaur/Vikizvornik
- procesaur/ZNANJE
- jerteh/SrpELTeC
language:
- sr
---

<table style="width:100%;height:100%">
  <tr>
<td colspan=2>
  <h2>Word2Vec</h2>
</td>
    </tr>
  <tr style="width:100%;height:100%">
    <td width=50%>     
      <p>обучаван над корпусом српског језика - 9.5 милијарди речи</p>
      <p>међу датотекама се налазе два модела (CBOW и SkipGram варијанте)</p>
    </td>
    <td>
      <p>trained on the Serbian language corpus - 9.5 billion words</p>
      <p>There are two models among the files (CBOW and SkipGram variants)</p>
    </td>
  </tr>
  </table>


```python
from gensim.models import Word2Vec
model = Word2Vec.load("TeslaW2V")
```





<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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  			style="display:DISPLAY_1; margin-left: auto; margin-right: auto; width: 92px; height:92px; border-radius: 50%; 
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          </div>
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    </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>

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       <p>Истраживање jе спроведено уз подршку Фонда за науку Републике Србиjе, #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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