Update README.md

README.md

@@ -13,13 +13,11 @@ from transformers import BertTokenizer
 from transformers import BertModel
 from sklearn.metrics.pairwise import cosine_similarity
 
-
 # model
 simcse_sup_path = "hellonlp/simcse-roberta-base-zh"
 tokenizer = BertTokenizer.from_pretrained(simcse_sup_path)
 MODEL = BertModel.from_pretrained(simcse_sup_path)
 
-
 def get_vector_simcse(sentence):
     """
     预测simcse的语义向量。
@@ -28,7 +26,6 @@ def get_vector_simcse(sentence):
     output = MODEL(input_ids)
     return output.last_hidden_state[:, 0].squeeze(0)
 
-
 embeddings = get_vector_simcse("武汉是一个美丽的城市。")
 print(embeddings.shape)
 #torch.Size([768])