Update README.md

README.md

@@ -21,13 +21,13 @@ from transformers import AutoTokenizer, AutoModel
 import torch
 
 #Mean Pooling - Take attention mask into account for correct averaging
-
 def mean_pooling(model_output, attention_mask):
     token_embeddings = model_output[0] #First element of model_output contains all token embeddings
     input_mask_expanded = attention_mask.unsqueeze(-1).expand(token_embeddings.size()).float()
     sum_embeddings = torch.sum(token_embeddings * input_mask_expanded, 1)
     sum_mask = torch.clamp(input_mask_expanded.sum(1), min=1e-9)
     return sum_embeddings / sum_mask
+
 #Sentences we want sentence embeddings for
 sentences = ['Привет! Как твои дела?',
              'А правда, что 42 твое любимое число?']