ku-nlp
/

bart-base-japanese

Text2Text Generation

Inference Endpoints

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Matttttttt commited on May 10, 2023

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@@ -18,8 +18,8 @@ This is a Japanese BART base model pre-trained on Japanese Wikipedia.
 You can use this model as follows:
 ```python
-from transformers import XLMRobertaTokenizer, MBartForConditionalGeneration
-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')

 You can use this model as follows:
 ```python
+from transformers import AutoTokenizer, MBartForConditionalGeneration
+tokenizer = AutoTokenizer.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')