update README

README.md

@@ -7,11 +7,11 @@ datasets:
 - wikipedia
 ---
 
-# Model Card for Japanese BART V2 base
+# Model Card for Japanese BART base
 
 ## Model description
 
-This is a Japanese BART V2 base model pre-trained on Japanese Wikipedia.
+This is a Japanese BART base model pre-trained on Japanese Wikipedia.
 
 ## How to use
 
@@ -19,8 +19,8 @@ You can use this model as follows:
 
 ```python
 from transformers import XLMRobertaTokenizer, MBartForConditionalGeneration
-tokenizer = XLMRobertaTokenizer.from_pretrained('ku-nlp/bart-v2-base-japanese')
-model = MBartForConditionalGeneration.from_pretrained('ku-nlp/bart-v2-base-japanese')
+tokenizer = XLMRobertaTokenizer.from_pretrained('ku-nlp/bart-base-japanese')
+model = MBartForConditionalGeneration.from_pretrained('ku-nlp/bart-base-japanese')
 sentence = '京都 大学 で 自然 言語 処理 を 専攻 する 。'  # input should be segmented into words by Juman++ in advance
 encoding = tokenizer(sentence, return_tensors='pt')
 ...