KoichiYasuoka commited on
Commit
1ec601b
1 Parent(s): 544cc06

initial release

Browse files
README.md ADDED
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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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+ license: "cc-by-sa-4.0"
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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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+
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+ # deberta-base-japanese-unidic
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+
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+ ## Model Description
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+
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+ This is a DeBERTa(V2) model pre-trained on 青空文庫 texts with BertJapaneseTokenizer. You can fine-tune `deberta-base-japanese-unidic` for downstream tasks, such as POS-tagging, dependency-parsing, and so on.
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+
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+ ## How to Use
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+
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+ ```py
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+ from transformers import AutoTokenizer,AutoModelForMaskedLM
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+ tokenizer=AutoTokenizer.from_pretrained("KoichiYasuoka/deberta-base-japanese-unidic")
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+ model=AutoModelForMaskedLM.from_pretrained("KoichiYasuoka/deberta-base-japanese-unidic")
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+ ```
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+
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+ [fugashi](https://pypi.org/project/fugashi) and [unidic-lite](https://pypi.org/project/unidic-lite) are required.
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+
config.json ADDED
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+ {
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+ "architectures": [
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+ "DebertaV2ForMaskedLM"
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+ ],
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+ "attention_probs_dropout_prob": 0.1,
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+ "bos_token_id": 0,
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+ "eos_token_id": 2,
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+ "hidden_act": "gelu",
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+ "hidden_dropout_prob": 0.1,
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+ "hidden_size": 768,
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+ "initializer_range": 0.02,
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+ "intermediate_size": 3072,
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+ "layer_norm_eps": 1e-07,
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+ "max_position_embeddings": 512,
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+ "max_relative_positions": -1,
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+ "model_type": "deberta-v2",
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+ "num_attention_heads": 12,
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+ "num_hidden_layers": 12,
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+ "pad_token_id": 1,
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+ "pooler_dropout": 0,
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+ "pooler_hidden_act": "gelu",
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+ "pooler_hidden_size": 768,
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+ "pos_att_type": null,
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+ "position_biased_input": true,
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+ "relative_attention": false,
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+ "tokenizer_class": "BertJapaneseTokenizer",
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+ "torch_dtype": "float32",
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+ "transformers_version": "4.19.2",
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+ "type_vocab_size": 0,
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+ "vocab_size": 32000
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+ }
pytorch_model.bin ADDED
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special_tokens_map.json ADDED
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+ {"unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]"}
tokenizer_config.json ADDED
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+ {"unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]", "do_lower_case": false, "do_word_tokenize": true, "do_subword_tokenize": true, "word_tokenizer_type": "mecab", "subword_tokenizer_type": "wordpiece", "never_split": ["[CLS]", "[PAD]", "[SEP]", "[UNK]", "[MASK]"], "mecab_kwargs": {"mecab_dic": "unidic_lite"}, "model_max_length": 512, "tokenizer_class": "BertJapaneseTokenizer"}
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vocab.txt ADDED
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