readme: Pretrained K-mHas with multi-label model with "koelectra-v3"
  
  You can use tokenizer of this model with "monologg/koelectra-v3-base-discriminator"
  
  dataset : https://huggingface.co/datasets/jeanlee/kmhas_korean_hate_speech
  
  pretrained_model : https://huggingface.co/monologg/koelectra-base-v3-discriminator
  
  label maps are like this.
  >>>
      {'origin': 0,
       'physical': 1,
       'politics': 2,
       'profanity': 3,
       'age': 4,
       'gender': 5,
       'race': 6,
       'religion': 7,
       'not_hate_speech': 8}
  
  You can use label map with below code.
  >
      
      from huggingface_hub import hf_hub_download
  
      repo_id = "JunHwi/kmhas_multilabel"
  
      filename = "kmhas_dict.pickle" # 위 repo_id에 업로드한 파일 이름
  
      label_dict = hf_hub_download(repo_id, filename)
  
      with open(label_dict, "rb") as f:
          label2num = pickle.load(f)