Update README.md

README.md

@@ -21,7 +21,7 @@ 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)
+    sum_mask = torch.clamp(input_mask_expanded.sum(1), min=1e-10)
     return sum_embeddings / sum_mask
 #Sentences we want sentence embeddings for
 sentences = ['Привет! Как твои дела?',