readme: ---
  language: ko
  tags:
  - bert
  - mrc
  datasets:
  - klue
  license: cc-by-nc-4.0
  ---
  
  ## Usage
  ```python
  # Load Transformers library
  import torch
  from transformers import AutoModelForQuestionAnswering, AutoTokenizer
  
  context = "your context"
  question = "your question"
  
  # Load fine-tuned MRC model by HuggingFace Model Hub
  HUGGINGFACE_MODEL_PATH = "bespin-global/klue-bert-base-mrc"
  tokenizer = AutoTokenizer.from_pretrained(HUGGINGFACE_MODEL_PATH )
  model = AutoModelForQuestionAnswering.from_pretrained(HUGGINGFACE_MODEL_PATH )
  
  # Encoding
  encodings = tokenizer(context, question, 
                        max_length=512, 
                        truncation=True,
                        padding="max_length", 
                        return_token_type_ids=False
                        )
  encodings = {key: torch.tensor([val]) for key, val in encodings.items()}             
  input_ids = encodings["input_ids"]
  attention_mask = encodings["attention_mask"]
  
  # Predict
  pred = model(input_ids, attention_mask=attention_mask)
  
  start_logits, end_logits = pred.start_logits, pred.end_logits
  token_start_index, token_end_index = start_logits.argmax(dim=-1), end_logits.argmax(dim=-1)
  pred_ids = input_ids[0][token_start_index: token_end_index + 1]
  
  # Decoding
  prediction = tokenizer.decode(pred_ids)
  ```
  
  ## Citing & Authors
  
  <!--- Describe where people can find more information -->
  [Jaehyeong](https://huggingface.co/jaehyeong) at [Bespin Global](https://www.bespinglobal.com/)