Update README.md
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README.md
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base_model:
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- FacebookAI/xlm-roberta-large
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---
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base_model:
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- FacebookAI/xlm-roberta-large
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---
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<table style="width:100%;height:100%">
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<tr>
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<td colspan=2>
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<h4><i class="highlight-container"><b class="highlight">TeslaXLM</b></i></h4>
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</td>
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</tr>
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<tr style="width:100%;height:100%">
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<td width=50%>
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<p>Вишејезични модел, 561 милион параметара</p>
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<p>Обучаван над корпусима српског и српскохрватског језика - 20 милијарди речи</p>
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<p>Једнака подршка уноса на ћирилици и латиници!</p>
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</td>
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<td>
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<p>Multilingual model, 561 million parameters</p>
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<p>Trained on Serbian and Serbo-Croatian corpora - 20 billion words</p>
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<p>Equal support for Cyrillic and Latin input!</p>
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</td>
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</tr>
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</table>
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```python
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>>> from transformers import pipeline
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>>> unmasker = pipeline('fill-mask', model='te-sla/teslaXLM')
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>>> unmasker("Kada bi čovek znao gde će pasti on bi<mask>.")
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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('te-sla/teslaXLM')
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>>> model = AutoModelForMaskedLM.from_pretrained('te-sla/teslaXLM', 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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<div class="inline-flex flex-col" style="line-height: 1.5;padding-right:50px">
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<div style="text-align: center; margin-top: 3px; font-size: 16px; font-weight: 800">Author</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:50px">
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<div style="text-align: center; margin-top: 3px; font-size: 16px; font-weight: 800">Author</div>
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<a href="https://huggingface.co/tanor">
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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-avatars.huggingface.co/v1/production/uploads/6409d3d71ee054d66a673701/KTOOnCRS9NhpAMZIvLlU7.png?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">Saša Petalinkar</div>
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<div>
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<a href="https://huggingface.co/tanor">
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<div style="text-align: center; font-size: 14px;">@tanor</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;">
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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://tesla.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: cover; background-image: url(https://cdn-avatars.huggingface.co/v1/production/uploads/63bc254fb8c61b8aa496a39b/TfM_-sc8-b34ddfhHBGTA.png?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">TESLA project</div>
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<div>
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<a href="https://huggingface.co/te-sla">
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<div style="text-align: center; font-size: 14px;">@te-sla</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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<br/><br/>
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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="background-color:#C6363C;width:100%;border:0px;height:30px"><td style="width:100vw"></td></tr>
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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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<table style="width:100%;height:100%">
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<tr style="width:100%;height:100%">
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<td width=50%>
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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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</td>
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<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>
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</td>
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</tr>
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</table>
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<style>
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.ffeat: {
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color:red
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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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p {
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font-size:14pt
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}
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</style>
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