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---
language:
- "th"
tags:
- "thai"
- "token-classification"
- "pos"
- "dependency-parsing"
base_model: KoichiYasuoka/roberta-base-thai-spm-upos
datasets:
- "universal_dependencies"
license: "apache-2.0"
pipeline_tag: "token-classification"
widget:
- text: "หลายหัวดีกว่าหัวเดียว"
---
# roberta-base-thai-spm-ud-goeswith
## Model Description
This is a RoBERTa model pre-trained on Thai Wikipedia texts for POS-tagging and dependency-parsing (using `goeswith` for subwords), derived from [roberta-base-thai-spm-upos](https://huggingface.co/KoichiYasuoka/roberta-base-thai-spm-upos).
## How to Use
```py
from transformers import pipeline
nlp=pipeline("universal-dependencies","KoichiYasuoka/roberta-base-thai-spm-ud-goeswith",trust_remote_code=True,aggregation_strategy="simple")
print(nlp("หลายหัวดีกว่าหัวเดียว"))
```
## 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.
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