readme: ---
  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/)