Update README.md

README.md

@@ -27,17 +27,17 @@ This repository provides a base-sized Japanese RoBERTa model. The model is provi
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 from transformers import T5Tokenizer, RobertaModel
 
-tokenizer = T5Tokenizer.from_pretrained("rinna/japanese-roberta-base")
+tokenizer = T5Tokenizer.from_pretrained("rinna/japanese-roberta-base", use_auth_token=True)
 tokenizer.do_lower_case = True  # due to some bug of tokenizer config loading
 
-model = RobertaModel.from_pretrained("rinna/japanese-roberta-base")
+model = RobertaModel.from_pretrained("rinna/japanese-roberta-base", use_auth_token=True)
 ~~~~
 
 # Model architecture
 A 12-layer, 768-hidden-size transformer-based masked language model.
 
 # Training
-The model was trained on [Japanese CC-100](http://data.statmt.org/cc-100/ja.txt.xz) and [Japanese Wikipedia](https://dumps.wikimedia.org/jawiki/) to optimize a masked language modelling objective on 8\\\\\\\\*V100 GPUs for around 15 days.
+The model was trained on [Japanese CC-100](http://data.statmt.org/cc-100/ja.txt.xz) and [Japanese Wikipedia](https://dumps.wikimedia.org/jawiki/) to optimize a masked language modelling objective on 8\\\\\\\\\\\\\\\\*V100 GPUs for around 15 days.
 
 # Tokenization
 The model uses a [sentencepiece](https://github.com/google/sentencepiece)-based tokenizer, the vocabulary was trained on the Japanese Wikipedia using the official sentencepiece training script.