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README.md
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- text: "早稲田 大学 で 自然 言語 処理 を [MASK] する 。"
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# nlp-waseda/roberta-base-japanese
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## Model description
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You can use this model for masked language modeling as follows:
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```python
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from transformers import AutoTokenizer, AutoModelForMaskedLM
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tokenizer = AutoTokenizer.from_pretrained("nlp-waseda/roberta-base-japanese")
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model = AutoModelForMaskedLM.from_pretrained("nlp-waseda/roberta-base-japanese")
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sentence = '早稲田 大学 で 自然 言語 処理 を [MASK] する 。' # input should be segmented into words by Juman++ in advance
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encoding = tokenizer(sentence, return_tensors='pt')
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- text: "早稲田 大学 で 自然 言語 処理 を [MASK] する 。"
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# nlp-waseda/roberta-base-japanese-with-auto-jumanpp
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## Model description
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You can use this model for masked language modeling as follows:
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```python
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from transformers import AutoTokenizer, AutoModelForMaskedLM
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tokenizer = AutoTokenizer.from_pretrained("nlp-waseda/roberta-base-japanese-with-auto-jumanpp")
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model = AutoModelForMaskedLM.from_pretrained("nlp-waseda/roberta-base-japanese-with-auto-jumanpp")
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sentence = '早稲田 大学 で 自然 言語 処理 を [MASK] する 。' # input should be segmented into words by Juman++ in advance
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encoding = tokenizer(sentence, return_tensors='pt')
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