initial release

README.md

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+---
+tags:
+- "japanese"
+- "question-answering"
+- "dependency-parsing"
+datasets:
+- "universal_dependencies"
+license: "cc-by-sa-4.0"
+pipeline_tag: "question-answering"
+widget:
+- text: "国語"
+  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"
+- text: "教科書"
+  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"
+- text: "の"
+  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"
+---
+
+# deberta-base-japanese-aozora-ud-head
+
+## Model Description
+
+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`.
+
+## How to Use
+
+```py
+import torch
+from transformers import AutoTokenizer,AutoModelForQuestionAnswering
+tokenizer=AutoTokenizer.from_pretrained("KoichiYasuoka/deberta-base-japanese-aozora-ud-head")
+model=AutoModelForQuestionAnswering.from_pretrained("KoichiYasuoka/deberta-base-japanese-aozora-ud-head")
+question="国語"
+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"
+inputs=tokenizer(question,context,return_tensors="pt",return_offsets_mapping=True)
+offsets=inputs.pop("offset_mapping").tolist()[0]
+outputs=model(**inputs)
+start,end=torch.argmax(outputs.start_logits),torch.argmax(outputs.end_logits)
+print(context[offsets[start][0]:offsets[end][-1]])
+```
+

config.json

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+{
+  "architectures": [
+    "DebertaV2ForQuestionAnswering"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "bos_token_id": 0,
+  "eos_token_id": 2,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 768,
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "layer_norm_eps": 1e-07,
+  "max_position_embeddings": 512,
+  "max_relative_positions": -1,
+  "model_type": "deberta-v2",
+  "num_attention_heads": 12,
+  "num_hidden_layers": 12,
+  "pad_token_id": 1,
+  "pooler_dropout": 0,
+  "pooler_hidden_act": "gelu",
+  "pooler_hidden_size": 768,
+  "pos_att_type": null,
+  "position_biased_input": true,
+  "relative_attention": false,
+  "tokenizer_class": "DebertaV2TokenizerFast",
+  "torch_dtype": "float32",
+  "transformers_version": "4.19.4",
+  "type_vocab_size": 0,
+  "vocab_size": 32000
+}

pytorch_model.bin

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+size 440178035

special_tokens_map.json

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+{"bos_token": "[CLS]", "eos_token": "[SEP]", "unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]"}

spm.model

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+oid sha256:01ba4719c80b6fe911b091a7c05124b64eeece964e09c058ef8f9805daca546b
+size 1

tokenizer_config.json

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+{"do_lower_case": false, "bos_token": "[CLS]", "eos_token": "[SEP]", "unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]", "split_by_punct": true, "keep_accents": true, "model_max_length": 512, "tokenizer_class": "DebertaV2TokenizerFast"}