dependency-parsing

README.md

@@ -6,6 +6,7 @@ tags:
 - "token-classification"
 - "pos"
 - "wikipedia"
+- "dependency-parsing"
 datasets:
 - "universal_dependencies"
 license: "cc-by-sa-4.0"
@@ -18,7 +19,7 @@ widget:
 
 ## Model Description
 
-This is a BERT model pre-trained on Japanese Wikipedia texts for POS-tagging, derived from [bert-base-japanese-char-extended](https://huggingface.co/KoichiYasuoka/bert-base-japanese-char-extended). Every word is tagged by [UPOS](https://universaldependencies.org/u/pos/) (Universal Part-Of-Speech).
+This is a BERT model pre-trained on Japanese Wikipedia texts for POS-tagging and dependency-parsing, derived from [bert-base-japanese-char-extended](https://huggingface.co/KoichiYasuoka/bert-base-japanese-char-extended). Every word is tagged by [UPOS](https://universaldependencies.org/u/pos/) (Universal Part-Of-Speech).
 
 ## How to Use
 
@@ -32,6 +33,14 @@ p=[model.config.id2label[q] for q in torch.argmax(model(tokenizer.encode(s,retur
 print(list(zip(s,p)))
 ```
 
+or
+
+```py
+import esupar
+nlp=esupar.load("KoichiYasuoka/bert-base-japanese-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