Update README.md

README.md

@@ -8,7 +8,7 @@
   
   ·easy to use,just like normal generation task.
   
-  ·input is sentence,and output is linearlize triples,such as input:姚明是一名NBA篮球运动员 output:[subj]姚明[obj]NBA[rel]公司[obj]篮球运动员[rel]职业(more details can read on REBEL paper)
+  ·input is sentence,and output is linearlize triples,such as input:姚明是一名NBA篮球运动员 output:[subj]姚明[obj]NBA[rel]公司[obj]篮球运动员[rel]职业
 
 
 using model：
@@ -25,5 +25,3 @@ tokenizer_kwargs = {
 tokenizer = BertTokenizer.from_pretrained(model_name, **tokenizer_kwargs)
 
 
-model = BartForConditionalGeneration.from_pretrained("fanxiao/rebel-base-chinese-cndbpedia")
-