Serbian
Word2VecSr / README.md
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---
license: cc-by-sa-4.0
datasets:
- procesaur/Vikipedija
- procesaur/Vikizvornik
- procesaur/ZNANJE
- jerteh/SrpELTeC
- procesaur/kisobran
language:
- sr
---
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<h4><i class="highlight-container"><b class="highlight">Word2Vec Sr</b></i></h4>
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<p>Обучаван над корпусом српског језика - 9.5 милијарди речи</p>
<p>Међу датотекама се налазе два модела (CBOW и SkipGram варијанте)</p>
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<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>
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```python
from gensim.models import Word2Vec
model = Word2Vec.load("TeslaSG")
examples = [
("dim", "zavesa"),
("staklo", "zavesa"),
("ormar", "zavesa"),
("prozor", "zavesa"),
("draperija", "zavesa")
]
for e in examples:
model.wv.similarity(e[0], e[1]))
```
```
0.5193785
0.5763144
0.59982747
0.6022524
0.7117646
```
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<div style="text-align: center; margin-top: 3px; font-size: 16px; font-weight: 800">Author</div>
<a href="https://huggingface.co/procesaur">
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<div style="text-align: center; font-size: 16px; font-weight: 800">Mihailo Škorić</div>
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<a href="https://huggingface.co/procesaur">
<div style="text-align: center; font-size: 14px;">@procesaur</div>
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<div style="text-align: center; margin-top: 3px; font-size: 16px; font-weight: 800">Computation</div>
<a href="https://tesla.rgf.bg.ac.rs">
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<div style="text-align: center; font-size: 16px; font-weight: 800">TESLA project</div>
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<a href="https://huggingface.co/te-sla">
<div style="text-align: center; font-size: 14px;">@te-sla</div>
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<p>Истраживање jе спроведено уз подршку Фонда за науку Републике Србиjе, #7276, Text Embeddings – Serbian Language Applications – TESLA</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</p>
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