KoichiYasuoka's picture
without ufal.chu-liu.edmonds
8c1a347
|
raw
history blame
No virus
1.11 kB
---
language:
- "vi"
tags:
- "vietnamese"
- "token-classification"
- "pos"
- "dependency-parsing"
base_model: vinai/phobert-base
datasets:
- "universal_dependencies"
license: "cc-by-sa-4.0"
pipeline_tag: "token-classification"
widget:
- text: "Hai cái đầu thì tốt hơn một"
---
# phobert-base-vietnamese-ud-goeswith
## Model Description
This is a PhoBERT model pre-trained on Vietnamese texts for POS-tagging and dependency-parsing (using `goeswith` for subwords), derived from [phobert-base](https://huggingface.co/vinai/phobert-base).
## How to Use
```py
from transformers import pipeline
nlp=pipeline("universal-dependencies","KoichiYasuoka/phobert-base-vietnamese-ud-goeswith",trust_remote_code=True,aggregation_strategy="simple")
print(nlp("Hai cái đầu thì tốt hơn một."))
```
## Reference
Koichi Yasuoka: [Sequence-Labeling RoBERTa Model for Dependency-Parsing in Classical Chinese and Its Application to Vietnamese and Thai](https://doi.org/10.1109/ICBIR57571.2023.10147628), ICBIR 2023: 8th International Conference on Business and Industrial Research (May 2023), pp.169-173.