Update README.md
Browse files
README.md
CHANGED
|
@@ -19,7 +19,7 @@ widget:
|
|
| 19 |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
|
| 20 |
should probably proofread and complete it, then remove this comment. -->
|
| 21 |
|
| 22 |
-
# xlm-roberta-ner-
|
| 23 |
|
| 24 |
(Japanese caption : 日本語の固有表現抽出のモデル)
|
| 25 |
|
|
@@ -47,7 +47,7 @@ Each token is labeled by :
|
|
| 47 |
```python
|
| 48 |
from transformers import pipeline
|
| 49 |
|
| 50 |
-
model_name = "tsmatz/xlm-roberta-ner-
|
| 51 |
classifier = pipeline("token-classification", model=model_name)
|
| 52 |
result = classifier("鈴木は4月の陽気の良い日に、鈴をつけて熊本県の阿蘇山に登った")
|
| 53 |
print(result)
|
|
|
|
| 19 |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
|
| 20 |
should probably proofread and complete it, then remove this comment. -->
|
| 21 |
|
| 22 |
+
# xlm-roberta-ner-japanese
|
| 23 |
|
| 24 |
(Japanese caption : 日本語の固有表現抽出のモデル)
|
| 25 |
|
|
|
|
| 47 |
```python
|
| 48 |
from transformers import pipeline
|
| 49 |
|
| 50 |
+
model_name = "tsmatz/xlm-roberta-ner-japanese"
|
| 51 |
classifier = pipeline("token-classification", model=model_name)
|
| 52 |
result = classifier("鈴木は4月の陽気の良い日に、鈴をつけて熊本県の阿蘇山に登った")
|
| 53 |
print(result)
|