Update README.md

README.md

@@ -33,14 +33,13 @@ You can use this model directly with a pipeline for text generation.
  {'generated_text': '昨日私は京都ではありませんが、自分の住んでる事について色々と'},
  {'generated_text': '昨日私は京都では地図を見ることしかしない、京福電車のホームで'},
  {'generated_text': '昨日私は京都でこみちに住み始めた時からある不思議な現象で、そ'}]
-...
 ```
 
 You can also use this model to get the features of a given text.
 
 ## Vocabulary
 
-A character-level vocabulary of size 6K is used. To be precise, rare characters may be split into bytes because byte-level byte-pair encoding (BPE) is used. The BPE tokenizer was trained on a small subset of the training data. Since the data were converted into a one-character-per-line format, merge operations never transgressed character boundaries.
+A character-level vocabulary of size 6K is used. To be precise, rare characters may be split into bytes because byte-level byte-pair encoding (BPE) is used. The BPE tokenizer was trained on a small subset of the training data. Since the data were converted into a one-character-per-line format, merge operations never go beyond character boundaries.
 
 ## Training data