|
--- |
|
language: |
|
- "be" |
|
- "bg" |
|
- "mk" |
|
- "ru" |
|
- "sr" |
|
- "uk" |
|
tags: |
|
- "belarusian" |
|
- "bulgarian" |
|
- "macedonian" |
|
- "russian" |
|
- "serbian" |
|
- "ukrainian" |
|
- "token-classification" |
|
- "pos" |
|
- "dependency-parsing" |
|
base_model: ai-forever/ruBert-large |
|
datasets: |
|
- "universal_dependencies" |
|
license: "cc-by-sa-4.0" |
|
pipeline_tag: "token-classification" |
|
--- |
|
|
|
# bert-large-slavic-cyrillic-upos |
|
|
|
## Model Description |
|
|
|
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/treebanks/sr_set/) [UD_Ukrainian](https://universaldependencies.org/treebanks/uk_iu/)) for POS-tagging and dependency-parsing, derived from [ruBert-large](https://huggingface.co/ai-forever/ruBert-large). Every word is tagged by [UPOS](https://universaldependencies.org/u/pos/) (Universal Part-Of-Speech). |
|
|
|
## How to Use |
|
|
|
```py |
|
from transformers import AutoTokenizer,AutoModelForTokenClassification |
|
tokenizer=AutoTokenizer.from_pretrained("KoichiYasuoka/bert-large-slavic-cyrillic-upos") |
|
model=AutoModelForTokenClassification.from_pretrained("KoichiYasuoka/bert-large-slavic-cyrillic-upos") |
|
``` |
|
|
|
or |
|
|
|
```py |
|
import esupar |
|
nlp=esupar.load("KoichiYasuoka/bert-large-slavic-cyrillic-upos") |
|
``` |
|
|
|
## See Also |
|
|
|
[esupar](https://github.com/KoichiYasuoka/esupar): Tokenizer POS-tagger and Dependency-parser with BERT/RoBERTa/DeBERTa models |
|
|
|
|
