| 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-ud-goeswith | |
| ## Model Description | |
| This is a BERT model pre-trained on Vietnamese texts for POS-tagging and dependency-parsing (using `goeswith` for subwords), derived from [vibert-base-cased](https://huggingface.co/FPTAI/vibert-base-cased). | |
| ## How to Use | |
| ```py | |
| from transformers import pipeline | |
| nlp=pipeline("universal-dependencies","KoichiYasuoka/bert-base-vietnamese-ud-goeswith",trust_remote_code=True,aggregation_strategy="simple") | |
| print(nlp("Hai cái đầu thì tốt hơn một.")) | |
| ``` | |