update

README.md

@@ -36,14 +36,45 @@ The copyright of the datasets belongs to the Institute of Linguistics, Academia
       AutoModel,
     )
 
-    tokenizer = AutoTokenizer.from_pretrained("ckiplab/oldhan-bert-base-chinese-ws")
-    model = AutoModel.from_pretrained("ckiplab/oldhan-bert-base-chinese-ws")
+    tokenizer = AutoTokenizer.from_pretrained("ckiplab/han-bert-base-chinese-ws")
+    model = AutoModel.from_pretrained("ckiplab/han-bert-base-chinese-ws")
     ```
 
 * Using our model for inference
     ```python
     >>> from transformers import pipeline
-    >>> classifier = pipeline("token-classification", model="ckiplab/oldhan-bert-base-chinese-ws")
+    >>> classifier = pipeline("token-classification", model="ckiplab/han-bert-base-chinese-ws")
     >>> classifier("帝堯曰放勳")
 
+    # output
+    [{'entity': 'B',
+    'score': 0.9999793,
+    'index': 1,
+    'word': '帝',
+    'start': 0,
+    'end': 1},
+    {'entity': 'I',
+    'score': 0.9915047,
+    'index': 2,
+    'word': '堯',
+    'start': 1,
+    'end': 2},
+    {'entity': 'B',
+    'score': 0.99992275,
+    'index': 3,
+    'word': '曰',
+    'start': 2,
+    'end': 3},
+    {'entity': 'B',
+    'score': 0.99905187,
+    'index': 4,
+    'word': '放',
+    'start': 3,
+    'end': 4},
+    {'entity': 'I',
+    'score': 0.96299917,
+    'index': 5,
+    'word': '勳',
+    'start': 4,
+    'end': 5}]
     ```