Update README.md

README.md

@@ -57,8 +57,9 @@ kao i korpus [PDRS 1.0](https://www.clarin.si/repository/xmlui/handle/11356/1752
 
 ```python
 >>> from transformers import pipeline
->>> generator = pipeline('fill-mask', model='jerteh/jerteh-355')
+>>> unmasker = pipeline('fill-mask', model='jerteh/jerteh-81')
 >>> unmasker("Kada bi čovek znao gde će pasti on bi<mask>.")
+>>> 
 ```
 
 ```
@@ -73,8 +74,8 @@ kao i korpus [PDRS 1.0](https://www.clarin.si/repository/xmlui/handle/11356/1752
 >>> from transformers import AutoTokenizer, AutoModelForMaskedLM
 >>> from torch import LongTensor, no_grad
 >>> from scipy import spatial
->>> tokenizer = AutoTokenizer.from_pretrained('jerteh/jerteh-355')
->>> model = AutoModelForMaskedLM.from_pretrained('jerteh/jerteh-355', output_hidden_states=True)
+>>> tokenizer = AutoTokenizer.from_pretrained('jerteh/jerteh-81')
+>>> model = AutoModelForMaskedLM.from_pretrained('jerteh/jerteh-81', output_hidden_states=True)
 >>> x = " pas"
 >>> y = " mačka"
 >>> z = " svemir"
@@ -83,12 +84,12 @@ kao i korpus [PDRS 1.0](https://www.clarin.si/repository/xmlui/handle/11356/1752
 >>> 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))
+>>>     print(spatial.distance.cosine(vektor_x, vektor_y))
+>>>     print(spatial.distance.cosine(vektor_x, vektor_z))
+>>> 
 ```
 
 ```