File size: 7,402 Bytes
f90a0d8 2792d46 a4922bd 2792d46 a4922bd 2792d46 b257dcc 2792d46 d76b4ba 2792d46 d76b4ba 91b1c8c d76b4ba 91b1c8c 62b8111 2792d46 275ddcc 2792d46 9278bed 2792d46 275ddcc 2792d46 275ddcc 2792d46 46fe86e c2f96de 46fe86e 2792d46 4efcc2d b257dcc cf46cdb b257dcc 4efcc2d 2792d46 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 |
---
license: cc-by-sa-4.0
datasets:
- procesaur/Vikipedija
language:
- sr
base_model:
- te-sla/Word2VecSr
tags:
- dict2vec
---
<table style="width:100%;height:100%">
<tr>
<td colspan=2>
<h4><i class="highlight-container"><b class="highlight">SerbDict2vec</b></i></h4>
</td>
</tr>
<tr style="width:100%;height:100%">
<td width=50%>
<p>Обучаван над корпусом српског језика Википедија, СрпКор2013 и део СрпКор2021 - 350 милиона речи</p>
</td>
<td>
<p>Trained on the Serbian language corpus compiled from srWikipedia, SrpKor2013, and part of SrpKor2021 - 350 million words</p>
</td>
</tr>
</table>
```python
from gensim.models import KeyedVectors
# Load the vectors
d2v_vectors = KeyedVectors.load("D:/modeli/dict2vec/SerbDict2vec")
# Check word vector
print(d2v_vectors["klijent"])
```
```
[-3.1600e-01 -3.4110e+00 1.2158e+01 3.7950e+00 6.1200e-01 -3.1000e-01
-9.7000e-02 -5.0000e-02 -5.2000e-02 -9.4000e-01 3.5600e-01 -6.0400e-01
-2.3700e-01 1.1600e-01 -4.5500e-01 1.6100e-01 2.2500e-01 -6.4700e-01
5.4600e-01 -7.8000e-02 3.5500e-01 5.8000e-02 -3.0000e-02 3.3000e-01
-1.5700e-01 -5.9700e-01 1.5000e-02 1.9600e-01 1.0000e-03 1.5800e-01
4.3300e-01 -5.0000e-03 -3.0700e-01 -2.6000e-01 -5.2500e-01 7.4000e-02
-2.7000e-02 1.8800e-01 5.6000e-02 -2.5200e-01 3.0700e-01 -4.3000e-02
5.9000e-02 -6.6000e-02 -1.0000e-02 1.3900e-01 7.1000e-02 -4.2000e-02
-3.2000e-02 -1.3100e-01 1.4000e-02 -8.9000e-02 -3.2200e-01 -6.2000e-02
-1.0500e-01 1.0800e-01 1.6100e-01 -1.3600e-01 -1.5400e-01 4.0000e-02
-5.1000e-02 1.1000e-02 2.6600e-01 3.0000e-03 -1.3800e-01 2.3400e-01
-2.9300e-01 1.5500e-01 2.5600e-01 2.7200e-01 1.2600e-01 1.9000e-01
-7.2000e-02 7.3000e-02 1.1700e-01 -1.1100e-01 5.9000e-02 -2.1100e-01
-1.8700e-01 -2.0000e-03 -3.6000e-02 -2.0400e-01 3.1300e-01 1.1600e-01
1.4800e-01 1.3000e-02 2.5200e-01 1.9700e-01 -6.7000e-02 4.5000e-02
1.3100e-01 -8.0000e-03 5.9000e-02 3.0800e-01 -3.2200e-01 -5.3000e-02
-1.5500e-01 -2.2100e-01 -7.6000e-02 1.3600e-01]
```
```python
# Find most similar words
print(d2v_vectors.most_similar("klijent", topn=5))
```
```
[('interfejs', 0.9971136450767517),
('mušterija', 0.996911883354187),
('provajder', 0.9968076348304749),
('sugrađanin', 0.9967014789581299),
('komšija', 0.9965119361877441)]
```
<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/rankas">
<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/63f8fa204ef4aacb65a00043/IlrBetI15qnGsc798R6tO.jpeg?w=200&h=200&f=face')">
</div>
</div>
</a>
<div style="text-align: center; font-size: 16px; font-weight: 800">Ranka Stanković</div>
<div>
<a href="https://huggingface.co/rankas">
<div style="text-align: center; font-size: 14px;">@rankas</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/rankas">
<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/no-auth/gfI5-noC3Si2qlV6vRiwL.png?w=200&h=200&f=face')">
</div>
</div>
</a>
<div style="text-align: center; font-size: 16px; font-weight: 800">Jovana Rađenović</div>
<div>
<a href="https://huggingface.co/JovanaR">
<div style="text-align: center; font-size: 14px;">@JovanaR</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/><br/>
## Cit.
```bibtex
@inproceedings{stankovic-dict2vec,
author = {Ranka Stanković, Jovana Rađenović, Mihailo Škorić, Marko Putniković},
title = {Learning Word Embeddings using Lexical Resources and Corpora},
booktitle = {15th International Conference on Information Society and Technology, ISIST 2025, Kopaonik},
year = {2025},
address = {Kopaonik, Belgrade}
url = {https://doi.org/10.5281/zenodo.15093900}
}
```
<div id="zastava">
<div class="grb">
<img src="https://www.ai.gov.rs/img/logo_60x120-2.png" style="position:relative; left:30px; z-index:10; height:85px">
</div>
<table width=100% style="border:0px">
<tr style="background-color:#C6363C;width:100%;border:0px;height:30px"><td style="width:100vw"></td></tr>
<tr style="background-color:#0C4076;width:100%;border:0px;height:30px"><td></td></tr>
<tr style="background-color:#ffffff;width:100%;border:0px;height:30px"><td></td></tr>
</table>
</div>
<table style="width:100%;height:100%">
<tr style="width:100%;height:100%">
<td width=50%>
<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>
<style>
.ffeat: {
color:red
}
.cover {
width: 100%;
margin-bottom: 5pt
}
.highlight-container, .highlight {
position: relative;
text-decoration:none
}
.highlight-container {
display: inline-block;
}
.highlight{
color:white;
text-transform:uppercase;
font-size: 16pt;
}
.highlight-container{
padding:5px 10px
}
.highlight-container:before {
content: " ";
display: block;
height: 100%;
width: 100%;
margin-left: 0px;
margin-right: 0px;
position: absolute;
background: #e80909;
transform: rotate(2deg);
top: -1px;
left: -1px;
border-radius: 20% 25% 20% 24%;
padding: 10px 18px 18px 10px;
}
div.grb, #zastava>table {
position:absolute;
top:0px;
left: 0px;
margin:0px
}
div.grb>img, #zastava>table{
margin:0px
}
#zastava {
position: relative;
margin-bottom:120px
}
p {
font-size:14pt
}
</style> |