dependency-parsing

README.md

@@ -5,6 +5,7 @@ tags:
 - "japanese"
 - "token-classification"
 - "pos"
+- "dependency-parsing"
 datasets:
 - "universal_dependencies"
 license: "cc-by-sa-4.0"
@@ -17,7 +18,7 @@ widget:
 
 ## Model Description
 
-This is a RoBERTa model pre-trained on Japanese 青空文庫 texts for POS-tagging, derived from [roberta-base-japanese-aozora](https://huggingface.co/KoichiYasuoka/roberta-base-japanese-aozora). Every long-unit-word is tagged by [UPOS](https://universaldependencies.org/u/pos/) (Universal Part-Of-Speech).
+This is a RoBERTa model pre-trained on Japanese 青空文庫 texts for POS-tagging and dependency-parsing, derived from [roberta-base-japanese-aozora](https://huggingface.co/KoichiYasuoka/roberta-base-japanese-aozora). Every long-unit-word is tagged by [UPOS](https://universaldependencies.org/u/pos/) (Universal Part-Of-Speech).
 
 ## How to Use
 
@@ -30,3 +31,16 @@ nlp=lambda x:[(x[t["start"]:t["end"]],t["entity_group"]) for t in pipeline(x)]
 print(nlp("国境の長いトンネルを抜けると雪国であった。"))
 ```
 
+or
+
+
+```py
+import esupar
+nlp=esupar.load("KoichiYasuoka/roberta-base-japanese-luw-upos")
+print(nlp("国境の長いトンネルを抜けると雪国であった。"))
+```
+
+## See Also
+
+[esupar](https://github.com/KoichiYasuoka/esupar): Tokenizer POS-tagger and Dependency-parser with BERT/RoBERTa models
+