dependency-parsing

README.md

@@ -6,6 +6,7 @@ tags:
 - "token-classification"
 - "pos"
 - "wikipedia"
+- "dependency-parsing"
 datasets:
 - "universal_dependencies"
 license: "apache-2.0"
@@ -16,7 +17,7 @@ pipeline_tag: "token-classification"
 
 ## Model Description
 
-This is a BERT model pre-trained on Chinese Wikipedia texts (both simplified and traditional) for POS-tagging, derived from [chinese-roberta-wwm-ext](https://huggingface.co/hfl/chinese-roberta-wwm-ext). Every word is tagged by [UPOS](https://universaldependencies.org/u/pos/) (Universal Part-Of-Speech).
+This is a BERT model pre-trained on Chinese Wikipedia texts (both simplified and traditional) for POS-tagging and dependency-parsing, derived from [chinese-roberta-wwm-ext](https://huggingface.co/hfl/chinese-roberta-wwm-ext). Every word is tagged by [UPOS](https://universaldependencies.org/u/pos/) (Universal Part-Of-Speech).
 
 ## How to Use
 
@@ -26,6 +27,13 @@ tokenizer=AutoTokenizer.from_pretrained("KoichiYasuoka/chinese-roberta-base-upos
 model=AutoModelForTokenClassification.from_pretrained("KoichiYasuoka/chinese-roberta-base-upos")
 ```
 
+or
+
+```py
+import esupar
+nlp=esupar.load("KoichiYasuoka/chinese-roberta-base-upos")
+```
+
 ## See Also
 
 [esupar](https://github.com/KoichiYasuoka/esupar): Tokenizer POS-tagger and Dependency-parser with BERT/RoBERTa models