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--- |
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license: cc-by-sa-4.0 |
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datasets: |
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- jerteh/cc100-sr-jerteh |
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- jerteh/SrpWiki |
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- jerteh/SrpELTeC |
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- srwac |
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- procesaur/STARS |
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language: |
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- sr |
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tags: |
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- srpski |
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- Serbian |
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- RoBERTa |
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- BERT |
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- MaskedLM |
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widget: |
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- text: Kada bi čovek znao gde će pasti on bi<mask>. |
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--- |
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<h4><i class="highlight-container"><b class="highlight">jerteh-355</b></i> — |
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Najveći BERT model specijalno obučen za srpski jezik.</h4> |
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<img src="cover.png" class="cover"> |
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<!--div id="zastava"> |
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<div class="grb"> |
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<img src="https://www.ai.gov.rs/img/logo_60x120-2.png" style="position:relative; left:30px; z-index:10; height:85px"> |
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</div> |
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<table width=100% style="border:0px"> |
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<tr style= |
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"background-color:#C6363C;width:100%;border:0px;height:30px"><td></td></tr |
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> |
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<tr style="background-color:#0C4076;width:100%;border:0px;height:30px"><td></td></tr> |
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<tr style="background-color:#ffffff;width:100%;border:0px;height:30px"><td></td></tr> |
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</table> |
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</div--> |
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<ul style="font-weight:bold"> |
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<li>Vektorizuje reči, ili dopunjava nedostajuće reči u tekstu</li> |
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<li>Zasnovan na RoBERTa-large arhitekturi, 355 miliona parametara</li> |
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<li>Obučavan na korpusu srpskog jezika veličine 4 milijarde tokena</li> |
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<li>Najbolji rezultati u modelovanju maskiranog jezika za srpski!</li> |
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<li>Jednaka podrška unosa i na ćirilici i na latinici!</li> |
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</ul> |
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</div> |
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Pored skupova navedenih u metapodacima, model je obučavan i na ostalim korpusima [Društva za jezičke resurse i tehnologije](https://jerteh.rs), |
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uključujući korpuse savremenog srpskog jezika: SrpKor2013 i SrpKor2021, |
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kao i korpus [PDRS 1.0](https://www.clarin.si/repository/xmlui/handle/11356/1752) razvijen od strane Instituta za Srpski jezik SANU. |
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## Upotreba |
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```python |
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>>> from transformers import pipeline |
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>>> unmasker = pipeline('fill-mask', model='jerteh/jerteh-355') |
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>>> unmasker("Kada bi čovek znao gde će pasti on bi<mask>.") |
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>>> |
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``` |
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``` |
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[{'score': 0.2131326049566269, 'token': 11379, 'token_str': ' pao', 'sequence': 'Kada bi čovek znao gde će pasti on bi pao.'}, |
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{'score': 0.18836458027362823, 'token': 20536, 'token_str': ' pobegao', 'sequence': 'Kada bi čovek znao gde će pasti on bi pobegao.'}, |
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{'score': 0.07937008887529373, 'token': 10799, 'token_str': ' umro', 'sequence': 'Kada bi čovek znao gde će pasti on bi umro.'}, |
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{'score': 0.04340635612607002, 'token': 7797, 'token_str': ' otišao', 'sequence': 'Kada bi čovek znao gde će pasti on bi otišao.'}, |
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{'score': 0.038474686443805695, 'token': 25984, 'token_str': ' odustao', 'sequence': 'Kada bi čovek znao gde će pasti on bi odustao.'}] |
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``` |
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```python |
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>>> from transformers import AutoTokenizer, AutoModelForMaskedLM |
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>>> from torch import LongTensor, no_grad |
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>>> from scipy import spatial |
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>>> tokenizer = AutoTokenizer.from_pretrained('jerteh/jerteh-355') |
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>>> model = AutoModelForMaskedLM.from_pretrained('jerteh/jerteh-355', output_hidden_states=True) |
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>>> x = " pas" |
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>>> y = " mačka" |
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>>> z = " svemir" |
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>>> tensor_x = LongTensor(tokenizer.encode(x, add_special_tokens=False)).unsqueeze(0) |
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>>> tensor_y = LongTensor(tokenizer.encode(y, add_special_tokens=False)).unsqueeze(0) |
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>>> tensor_z = LongTensor(tokenizer.encode(z, add_special_tokens=False)).unsqueeze(0) |
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>>> model.eval() |
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>>> with no_grad(): |
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>>> vektor_x = model(input_ids=tensor_x).hidden_states[-1].squeeze() |
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>>> vektor_y = model(input_ids=tensor_y).hidden_states[-1].squeeze() |
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>>> vektor_z = model(input_ids=tensor_z).hidden_states[-1].squeeze() |
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>>> print(spatial.distance.cosine(vektor_x, vektor_y)) |
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>>> print(spatial.distance.cosine(vektor_x, vektor_z)) |
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>>> |
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``` |
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``` |
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0.029090166091918945 |
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0.0369451642036438 |
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``` |
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<h4>U slučaju potrebe za bržim modelom, pogledajte <a href="https://huggingface.co/jerteh/jerteh-81" class="highlight-container"> |
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<b class="highlight">jerteh-81</b></a> — mali BERT model za srpski jezik.</h4> |
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<h4>U slučaju potrebe za generativnim modelom, pogledajte <a href="https://huggingface.co/jerteh/gpt2-orao" class="highlight-container"> |
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<b class="highlight">gpt2-orao</b></a> i <a href="https://huggingface.co/jerteh/gpt2-vrabac" class="highlight-container"> |
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<b class="highlight">gpt2-vrabac</b></a></h4> |
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<div class="inline-flex flex-col" style="line-height: 1.5;padding-right:40px"> |
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<div style="text-align: center; margin-top: 3px; font-size: 16px; font-weight: 800">Autor</div> |
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<a href="https://huggingface.co/procesaur"> |
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<div class="flex"> |
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<div |
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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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background-size: cover; background-image: url('https://cdn-uploads.huggingface.co/production/uploads/1673534533167-63bc254fb8c61b8aa496a39b.jpeg?w=200&h=200&f=face')"> |
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</div> |
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</div> |
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</a> |
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<div style="text-align: center; font-size: 16px; font-weight: 800">Mihailo Škorić</div> |
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<div> |
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<a href="https://huggingface.co/procesaur"> |
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<div style="text-align: center; font-size: 14px;">@procesaur</div> |
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</a> |
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</div> |
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</div> |
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</div> |
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<div class="inline-flex flex-col" style="line-height: 1.5;padding-right:40px"> |
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<div style="text-align: center; margin-top: 3px; font-size: 16px; font-weight: 800">Computation</div> |
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<a href="https://rgf.bg.ac.rs/"> |
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<div class="flex"> |
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<div |
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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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background-size: contain; background-image: url(https://rgf.bg.ac.rs/slike/Rgf-logo.jpg);background-repeat: no-repeat; |
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background-position: center;"> |
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</div> |
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</div> |
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</a> |
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<div style="text-align: center; font-size: 16px; font-weight: 800" title="Rudarsko-Geološki fakultet Univerziteta u Beogradu">Rudarsko-Geološki fakultet</div> |
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<div> |
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<a href="https://www.ai.gov.rs/"> |
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<div style="text-align: center; font-size: 14px;">rgf.bg.ac.rs</div> |
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</a> |
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</div> |
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</div> |
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</div> |
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<div class="inline-flex flex-col" style="line-height: 1.5;padding-right:40px"> |
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<div style="text-align: center; margin-top: 3px; font-size: 16px; font-weight: 800">Data</div> |
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<a href="https://jerteh.rs/"> |
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<div class="flex"> |
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<div |
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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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background-size: contain; background-image: url(https://cdn-avatars.huggingface.co/v1/production/uploads/1673601491672-63bc254fb8c61b8aa496a39b.png?w=200&h=200&f=face);background-repeat: no-repeat; |
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background-position: center;"> |
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</div> |
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</div> |
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</a> |
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<div style="text-align: center; font-size: 16px; font-weight: 800" title="Društvo za jezičke resurse i tehnologije">JeRTeh</div> |
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<div> |
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<a href="https://huggingface.co/jerteh"> |
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<div style="text-align: center; font-size: 14px;">@jerteh</div> |
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</a> |
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</div> |
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</div> |
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</div> |
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## Citiranje |
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```bibtex |
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@article{skoric24modeli, |
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author = {Mihailo \vSkori\'c}, |
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title = {Novi jezi\vcki modeli za srpski jezik}, |
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journal = {Infoteka}, |
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volume = {24}, |
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issue = {1}, |
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year = {2024}, |
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publisher = {Zajednica biblioteka univerziteta u Srbiji, Beograd}, |
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url = {https://arxiv.org/abs/2402.14379} |
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} |
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``` |
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<style> |
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.ffeat: { |
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color:red |
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} |
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|
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.cover { |
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width: 100%; |
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margin-bottom: 5pt |
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} |
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.highlight-container, .highlight { |
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position: relative; |
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text-decoration:none |
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} |
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.highlight-container { |
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display: inline-block; |
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} |
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.highlight{ |
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color:white; |
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text-transform:uppercase; |
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font-size: 16pt; |
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} |
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.highlight-container{ |
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padding:5px 10px |
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} |
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.highlight-container:before { |
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content: " "; |
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display: block; |
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height: 100%; |
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width: 100%; |
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margin-left: 0px; |
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margin-right: 0px; |
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position: absolute; |
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background: #e80909; |
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transform: rotate(2deg); |
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top: -1px; |
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left: -1px; |
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border-radius: 20% 25% 20% 24%; |
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padding: 10px 18px 18px 10px; |
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} |
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div.grb, #zastava>table { |
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position:absolute; |
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top:0px; |
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left: 0px; |
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margin:0px |
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} |
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div.grb>img, #zastava>table{ |
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margin:0px |
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} |
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#zastava { |
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position: relative; |
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margin-bottom:120px |
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} |
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</style> |