Update README.md

README.md

@@ -27,7 +27,8 @@ BERT model specijalno obučen za srpski jezik.</h4>
     <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></td></tr>
+    <tr style=
+"background-color:#C6363C;width:100%;border:0px;height:30px"><td></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>
@@ -57,28 +58,23 @@ kao i korpus [PDRS 1.0](https://www.clarin.si/repository/xmlui/handle/11356/1752
  {'score': 0.0532902330160141, 'token': 998, 'token_str': ' rekao', 'sequence': 'Kada bi čovek znao gde će pasti on bi rekao.'}]
 ```
 
-```
+```python
 >>> from transformers import AutoTokenizer, AutoModelForMaskedLM
 >>> from torch import LongTensor, no_grad
 >>> from scipy import spatial
-
 >>> tokenizer = AutoTokenizer.from_pretrained('bert modeli/bertovic-base')
 >>> model = AutoModelForMaskedLM.from_pretrained('bert modeli/bertovic-base', 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))
 ```