readme: ---
  license: mit
  ---
  # Model description 
  LegalBert is a BERT-base-cased model fine-tuned on a subset of the `case.law` corpus. Further details can be found in this paper:
  
  [A Dataset for Statutory Reasoning in Tax Law Entailment and Question Answering](http://ceur-ws.org/Vol-2645/paper5.pdf)  
  Nils Holzenberger, Andrew Blair-Stanek and Benjamin Van Durme  
  *Proceedings of the 2020 Natural Legal Language Processing (NLLP) Workshop, 24 August 2020*
  
  # Usage
  ```
  from transformers import AutoModel, AutoTokenizer
  model = AutoModel.from_pretrained("jhu-clsp/LegalBert")
  tokenizer = AutoTokenizer.from_pretrained("jhu-clsp/LegalBert")
  ```
  
  # Citation
  ```
  @inproceedings{holzenberger20dataset,
    author    = {Nils Holzenberger and
                 Andrew Blair{-}Stanek and
                 Benjamin Van Durme},
    title     = {A Dataset for Statutory Reasoning in Tax Law Entailment and Question
                 Answering},
    booktitle = {Proceedings of the Natural Legal Language Processing Workshop 2020
                 co-located with the 26th {ACM} {SIGKDD} International Conference on
                 Knowledge Discovery {\&} Data Mining {(KDD} 2020), Virtual Workshop,
                 August 24, 2020},
    series    = {{CEUR} Workshop Proceedings},
    volume    = {2645},
    pages     = {31--38},
    publisher = {CEUR-WS.org},
    year      = {2020},
    url       = {http://ceur-ws.org/Vol-2645/paper5.pdf},
  }
  ```
  