Update README.md

README.md

@@ -12,6 +12,35 @@ For further details, refer to our paper on Journalism: [News comment sections an
 * This model is a finetuned model based on ETRI\'s KorBERT. 
 
 
+### How to use
+* The model requires an edited version of the transformers class `BertTokenizer`, which can be found in the file `KorBertTokenizer.py`.
+* Usage example:
+
+~~~python
+from KorBertTokenizer import KorBertTokenizer
+from transformers import BertForSequenceClassification
+import torch
+
+tokenizer = KorBertTokenizer.from_pretrained('model\\')
+model = BertForSequenceClassification.from_pretrained('model\\')
+
+def classify(text):
+    inputs = tokenizer(text, padding='max_length', max_length=70, return_tensors='pt')
+
+    with torch.no_grad():
+        logits=model(**inputs).logits
+        predicted_class_id = logits.argmax().item()
+        return model.config.id2label[predicted_class_id]
+
+
+input_strings = ['좌파가 나라 경제 안보 말아먹는다',
+                 '수꼴들은 나라 일본한테 팔아먹었냐']
+
+for input_string in input_strings:
+    print('===\n입력 텍스트: {}\n분류 결과: {}\n==='.format(input_string, classify(input_string)))
+~~~
+
+
 ### Model performance
 
 * Accuracy: 0.8322