Update README.md

README.md

@@ -65,7 +65,7 @@ with torch.no_grad():
 
 Before applying BPE to the pre-training corpus of English Tweets, we tokenized these  Tweets using `TweetTokenizer` from the NLTK toolkit and used the `emoji` package to translate emotion icons into text strings (here, each icon is referred to as a word token).   We also normalized the Tweets by converting user mentions and web/url links into special tokens `@USER` and `HTTPURL`, respectively. Thus it is recommended to also apply the same pre-processing step for BERTweet-based downstream applications w.r.t. the raw input Tweets. 
 
-For "`vinai/bertweet-large`", given the raw input Tweets, to obtain the same pre-processing output, users could employ our  [TweetNormalizer](https://github.com/VinAIResearch/BERTweet/blob/master/TweetNormalizer.py) module.
+For `vinai/bertweet-large`, given the raw input Tweets, to obtain the same pre-processing output, users could employ our  [TweetNormalizer](https://github.com/VinAIResearch/BERTweet/blob/master/TweetNormalizer.py) module.
 
 - Installation: `pip3 install nltk emoji`