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--- |
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tags: |
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- "japanese" |
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- "question-answering" |
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- "dependency-parsing" |
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datasets: |
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- "universal_dependencies" |
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license: "cc-by-sa-4.0" |
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pipeline_tag: "question-answering" |
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widget: |
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- text: "国語" |
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context: "全学年にわたって小学校の国語の教科書に挿し絵が用いられている" |
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- text: "教科書" |
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context: "全学年にわたって小学校の国語の教科書に挿し絵が用いられている" |
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- text: "の" |
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context: "全学年にわたって小学校の国語[MASK]教科書に挿し絵が用いられている" |
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--- |
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# deberta-base-japanese-aozora-ud-head |
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## Model Description |
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This is a DeBERTa(V2) model pretrained on 青空文庫 for dependency-parsing (head-detection on long-unit-words) as question-answering, derived from [deberta-base-japanese-aozora](https://huggingface.co/KoichiYasuoka/deberta-base-japanese-aozora) and [UD_Japanese-GSDLUW](https://huggingface.co/UniversalDependencies/UD_Japanese-GSDLUW). Use [MASK] inside `context` to avoid ambiguity when specifing a multiple-used word as `question`. |
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## How to Use |
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```py |
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import torch |
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from transformers import AutoTokenizer,AutoModelForQuestionAnswering |
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tokenizer=AutoTokenizer.from_pretrained("KoichiYasuoka/deberta-base-japanese-aozora-ud-head") |
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model=AutoModelForQuestionAnswering.from_pretrained("KoichiYasuoka/deberta-base-japanese-aozora-ud-head") |
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question="国語" |
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context="全学年にわたって小学校の国語の教科書に挿し絵が用いられている" |
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inputs=tokenizer(question,context,return_tensors="pt",return_offsets_mapping=True) |
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offsets=inputs.pop("offset_mapping").tolist()[0] |
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outputs=model(**inputs) |
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start,end=torch.argmax(outputs.start_logits),torch.argmax(outputs.end_logits) |
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print(context[offsets[start][0]:offsets[end][-1]]) |
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``` |
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