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--- |
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language: |
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- "be" |
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- "bg" |
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- "ru" |
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- "sr" |
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- "uk" |
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tags: |
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- "belarusian" |
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- "bulgarian" |
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- "russian" |
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- "serbian" |
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- "ukrainian" |
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- "token-classification" |
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- "pos" |
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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: "token-classification" |
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--- |
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# bert-base-slavic-cyrillic-upos |
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## Model Description |
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This is a BERT model pre-trained with Slavic-Cyrillic ([UD_Belarusian](https://universaldependencies.org/be/) [UD_Bulgarian](https://universaldependencies.org/bg/) [UD_Russian](https://universaldependencies.org/ru/) [UD_Serbian](https://universaldependencies.org/sr/) [UD_Ukrainian](https://universaldependencies.org/uk/)) for POS-tagging and dependency-parsing, derived from [ruBert-base](https://huggingface.co/sberbank-ai/ruBert-base). Every word is tagged by [UPOS](https://universaldependencies.org/u/pos/) (Universal Part-Of-Speech). |
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## How to Use |
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```py |
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from transformers import AutoTokenizer,AutoModelForTokenClassification |
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tokenizer=AutoTokenizer.from_pretrained("KoichiYasuoka/bert-base-slavic-cyrillic-upos") |
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model=AutoModelForTokenClassification.from_pretrained("KoichiYasuoka/bert-base-slavic-cyrillic-upos") |
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``` |
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or |
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```py |
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import esupar |
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nlp=esupar.load("KoichiYasuoka/bert-base-slavic-cyrillic-upos") |
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``` |
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## See Also |
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[esupar](https://github.com/KoichiYasuoka/esupar): Tokenizer POS-tagger and Dependency-parser with BERT/RoBERTa models |
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