README.md

---
license: cc-by-sa-4.0
datasets:
- procesaur/ZNANJE
- procesaur/STARS
- procesaur/Vikipedija
- procesaur/Vikizvornik
- jerteh/SrpELTeC
- procesaur/kisobran
language:
- sr
- hr
base_model:
- FacebookAI/xlm-roberta-large
---

<table style="width:100%;height:100%">
  <tr>
<td colspan=2>
  <h4><i class="highlight-container"><b class="highlight">TeslaXLM</b></i></h4>
</td>
    </tr>
  <tr style="width:100%;height:100%">
    <td width=50%>
      <p>Вишејезични модел, 561 милион параметара</p>
      <p>Обучаван над корпусима српског и српскохрватског језика - 20 милијарди речи</p>
      <p>Једнака подршка уноса на ћирилици и латиници!</p>
    </td>
    <td>
      <p>Multilingual model, 561 million parameters</p>
      <p>Trained on Serbian and Serbo-Croatian corpora - 20 billion words</p>
      <p>Equal support for Cyrillic and Latin input!</p>
    </td>
  </tr>
  </table>

```python
>>> from transformers import pipeline
>>> unmasker = pipeline('fill-mask', model='te-sla/teslaXLM')
>>> unmasker("Kada bi čovek znao gde će pasti on bi<mask>.")
```

```python
>>> from transformers import AutoTokenizer, AutoModelForMaskedLM
>>> from torch import LongTensor, no_grad
>>> from scipy import spatial
>>> tokenizer = AutoTokenizer.from_pretrained('te-sla/teslaXLM')
>>> model = AutoModelForMaskedLM.from_pretrained('te-sla/teslaXLM', output_hidden_states=True)
>>> x = " pas"
>>> y = " mačka"
>>> z = " svemir"
>>> tensor_x = LongTensor(tokenizer.encode(x, add_special_tokens=False)).unsqueeze(0)
>>> tensor_y = LongTensor(tokenizer.encode(y, add_special_tokens=False)).unsqueeze(0)
>>> tensor_z = LongTensor(tokenizer.encode(z, add_special_tokens=False)).unsqueeze(0)
>>> model.eval()
>>> with no_grad():
>>>     vektor_x = model(input_ids=tensor_x).hidden_states[-1].squeeze()
>>>     vektor_y = model(input_ids=tensor_y).hidden_states[-1].squeeze()
>>>     vektor_z = model(input_ids=tensor_z).hidden_states[-1].squeeze()
>>>     print(spatial.distance.cosine(vektor_x, vektor_y))
>>>     print(spatial.distance.cosine(vektor_x, vektor_z))
```

<table style="width:100%;height:100%">
<tr>
<td width=50%>
  <h5><i class="highlight-container"><b class="highlight">Евалуација XLMR модела за српски језик</b></i></h4>
</td>
<td>
  <h5><i class="highlight-container"><b class="highlight">Serbian XLMR models evaluation results</b></i></h4>
</td>
</tr>
  <tr colspan=2 style="width:100%;height:100%">
    <td colspan=2 >
    <img src="xlm-fm.png" class="cover" style="max-width:650px">
      <img src="xlm-pr.png" class="cover" style="max-width:650px">
      <img src="xlm-ds.png" class="cover" style="max-width:650px">
    </td>
  </tr>
  </table>

<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:50px">
  <div style="text-align: center; margin-top: 3px; font-size: 16px; font-weight: 800">Author</div>
    <a href="https://huggingface.co/tanor">  
      <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('https://cdn-avatars.huggingface.co/v1/production/uploads/6409d3d71ee054d66a673701/KTOOnCRS9NhpAMZIvLlU7.png?w=200&h=200&f=face')">
          </div>
      </div>
    </a>
    <div style="text-align: center; font-size: 16px; font-weight: 800">Saša Petalinkar</div>
    <div>  
      <a href="https://huggingface.co/tanor">
      	<div style="text-align: center; font-size: 14px;">@tanor</div>
      </a>
    </div>
  </div>
</div>

<div class="inline-flex flex-col" style="line-height: 1.5;"> 
  <div style="text-align: center; margin-top: 3px; font-size: 16px; font-weight: 800">Computation</div>
    <a href="https://tesla.rgf.bg.ac.rs">  
      <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(https://cdn-avatars.huggingface.co/v1/production/uploads/63bc254fb8c61b8aa496a39b/TfM_-sc8-b34ddfhHBGTA.png?w=200&h=200&f=face)">
          </div>
      </div>
    </a>
    <div style="text-align: center; font-size: 16px; font-weight: 800">TESLA project</div>
    <div>  
      <a href="https://huggingface.co/te-sla">
      	<div style="text-align: center; font-size: 14px;">@te-sla</div>
      </a>
    </div>
  </div>
</div>
<br/>

## Cit.

```bibtex
@inproceedings{skoricxlm,
  author    = {Mihailo Škorić, Saša Petalinkar},
  title     = {New XLM-R-based language models for Serbian and Serbo-Croatian},
  booktitle   = {ARTIFICAL INTELLIGENCE CONFERENCE},
  year      = {2024},
  address = {Belgrade}
  publisher = {SASA, Belgrade},
  url       = {}
}
```
<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>
  </tr>
</table>



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