| language: | |
| - "zh" | |
| tags: | |
| - "chinese" | |
| - "token-classification" | |
| - "pos" | |
| - "dependency-parsing" | |
| base_model: KoichiYasuoka/deberta-large-chinese-erlangshen-upos | |
| datasets: | |
| - "universal_dependencies" | |
| license: "apache-2.0" | |
| pipeline_tag: "token-classification" | |
| # deberta-large-chinese-erlangshen-ud-goeswith | |
| ## Model Description | |
| This is a DeBERTa(V2) model pre-trained on Chinese texts (both simplified and traditional) for POS-tagging and dependency-parsing (using `goeswith` for subwords), derived from [deberta-large-chinese-erlangshen-upos](https://huggingface.co/KoichiYasuoka/deberta-large-chinese-erlangshen-upos). | |
| ## How to Use | |
| ```py | |
| from transformers import pipeline | |
| nlp=pipeline("universal-dependencies","KoichiYasuoka/deberta-large-chinese-erlangshen-ud-goeswith",trust_remote_code=True,aggregation_strategy="simple") | |
| print(nlp("我把这本书看完了")) | |
| ``` | |