dependency-parsing

README.md

@@ -6,6 +6,7 @@ tags:
 - "token-classification"
 - "pos"
 - "wikipedia"
+- "dependency-parsing"
 datasets:
 - "universal_dependencies"
 license: "apache-2.0"
@@ -18,7 +19,7 @@ widget:
 
 ## Model Description
 
-This is a BERT model pre-trained on Thai Wikipedia texts for POS-tagging, derived from [bert-base-th-cased](https://huggingface.co/Geotrend/bert-base-th-cased). Every word is tagged by [UPOS](https://universaldependencies.org/u/pos/) (Universal Part-Of-Speech).
+This is a BERT model pre-trained on Thai Wikipedia texts for POS-tagging and dependency-parsing, derived from [bert-base-th-cased](https://huggingface.co/Geotrend/bert-base-th-cased). Every word is tagged by [UPOS](https://universaldependencies.org/u/pos/) (Universal Part-Of-Speech).
 
 ## How to Use
 
@@ -29,3 +30,14 @@ tokenizer=AutoTokenizer.from_pretrained("KoichiYasuoka/bert-base-thai-upos")
 model=AutoModelForTokenClassification.from_pretrained("KoichiYasuoka/bert-base-thai-upos")
 ```
 
+or
+
+```py
+import esupar
+nlp=esupar.load("KoichiYasuoka/bert-base-thai-upos")
+```
+
+## See Also
+
+[esupar](https://github.com/KoichiYasuoka/esupar): Tokenizer POS-tagger and Dependency-parser with BERT/RoBERTa models
+