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---
language:
- "vi"
tags:
- "vietnamese"
- "token-classification"
- "pos"
- "dependency-parsing"
base_model: FPTAI/vibert-base-cased
datasets:
- "universal_dependencies"
license: "cc-by-sa-4.0"
pipeline_tag: "token-classification"
widget:
- text: "Hai cái đầu thì tốt hơn một."
---
# bert-base-vietnamese-upos
## Model Description
This is a BERT model pre-trained on Vietnamese texts for POS-tagging and dependency-parsing, derived from [vibert-base-cased](https://huggingface.co/FPTAI/vibert-base-cased). Every word is tagged by [UPOS](https://universaldependencies.org/u/pos/)(Universal Part-Of-Speech).
## How to Use
```py
from transformers import AutoTokenizer,AutoModelForTokenClassification,TokenClassificationPipeline
tokenizer=AutoTokenizer.from_pretrained("KoichiYasuoka/bert-base-vietnamese-upos")
model=AutoModelForTokenClassification.from_pretrained("KoichiYasuoka/bert-base-vietnamese-upos")
pipeline=TokenClassificationPipeline(tokenizer=tokenizer,model=model,aggregation_strategy="simple")
nlp=lambda x:[(x[t["start"]:t["end"]],t["entity_group"]) for t in pipeline(x)]
print(nlp("Hai cái đầu thì tốt hơn một."))
```
or
```py
import esupar
nlp=esupar.load("KoichiYasuoka/bert-base-vietnamese-upos")
print(nlp("Hai cái đầu thì tốt hơn một."))
```
## See Also
[esupar](https://github.com/KoichiYasuoka/esupar): Tokenizer POS-tagger and Dependency-parser with BERT/RoBERTa/DeBERTa models
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