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--- |
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language: |
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- "ja" |
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tags: |
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- "japanese" |
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- "masked-lm" |
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- "modernbert" |
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datasets: |
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- "globis-university/aozorabunko-clean" |
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license: "apache-2.0" |
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pipeline_tag: "fill-mask" |
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mask_token: "[MASK]" |
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widget: |
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- text: "日本に着いたら[MASK]を訪ねなさい。" |
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--- |
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# modernbert-large-japanese-aozora |
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## Model Description |
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This is a ModernBERT model pre-trained on 青空文庫 texts. NVIDIA A100-SXM4-40GB×8 took 10 hours 5 minutes for training. You can fine-tune `modernbert-large-japanese-aozora` for downstream tasks, such as [POS-tagging](https://huggingface.co./KoichiYasuoka/modernbert-large-japanese-aozora-upos), [dependency-parsing](https://huggingface.co./KoichiYasuoka/modernbert-large-japanese-aozora-ud-square), and so on. |
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## How to Use |
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```py |
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from transformers import AutoTokenizer,AutoModelForMaskedLM |
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tokenizer=AutoTokenizer.from_pretrained("KoichiYasuoka/modernbert-large-japanese-aozora") |
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model=AutoModelForMaskedLM.from_pretrained("KoichiYasuoka/modernbert-large-japanese-aozora",trust_remote_code=True) |
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``` |
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### Reference |
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安岡孝一: 青空文庫ModernBERTモデルによる国語研長単位係り受け解析, 情報処理学会研究報告, Vol.2025-CH-137『人文科学とコンピュータ』, No.10 (2025年2月8日), pp.1-7. |
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