Update README.md

README.md

@@ -1,3 +1,33 @@
 ---
 license: cc-by-nc-nd-4.0
+language: ko
+widget:
+  - text: 피고인은 2022. 11. 14. 혈중알콜농도 0.123%의 술에 취한 상태로 승용차를 운전하였다.
 ---
+# Model information
+KLAID(Korean Legal Artificial Intelligence Datasets) LJP classification model based on pretrained KLUE RoBERTa-base. See more information about KLUE: [Github](https://github.com/KLUE-benchmark/KLUE) and [Paper](https://arxiv.org/abs/2105.09680) for more details.
+## How to use
+_NOTE:_ Use `BertTokenizer` instead of RobertaTokenizer and RobertaForSequenceClassification. (`AutoTokenizer` will load `BertTokenizer`)
+```python
+import numpy as np
+from transformers import AutoTokenizer, AutoModelForSequenceClassification
+tokenizer = AutoTokenizer.from_pretrained("lawcompany/KLAID_LJP_base")
+model = AutoModelForSequenceClassification.from_pretrained("lawcompany/KLAID_LJP_base")
+model.eval()
+input_data = tokenizer("피고인은 2022. 11. 14. 혈중알콜농도 0.123%의 술에 취한 상태로 승용차를 운전하였다.", 
+                       max_length=512, 
+                       return_tensors="pt")
+logits = model(**input_data).logits.detach().numpy()
+pred = np.argmax(logits)
+# output
+# 7
+```
+
+## Licensing information
+Copyright 2022-present [Law&Company Co. Ltd.](https://career.lawcompany.co.kr/)
+
+Licensed under the CC-BY-NC-ND-4.0
+
+## Other Inquiries
+- **Email:** [klaid@lawcompany.co.kr](klaid@lawcompany.co.kr)
+- **Homepage:** [https://klaid.net/](https://klaid.net/)