readme: ---
  language: ko
  tags:
  - gpt2
  - conversational
  license: cc-by-nc-sa-4.0
  ---
  ## Ko-DialoGPT
  
  
  ### How to use
  ```python
  from transformers import PreTrainedTokenizerFast, GPT2LMHeadModel
  import torch
  
  
  device = 'cuda' if torch.cuda.is_available() else 'cpu'
  
  tokenizer = PreTrainedTokenizerFast.from_pretrained('byeongal/Ko-DialoGPT')
  model = GPT2LMHeadModel.from_pretrained('byeongal/Ko-DialoGPT').to(device)
  
  past_user_inputs = []
  generated_responses = []
  
  while True:
      user_input = input(">> User:")
      if user_input == 'bye':
          break
      text_idx = tokenizer.encode(user_input + tokenizer.eos_token, return_tensors='pt')
      for i in range(len(generated_responses)-1, len(generated_responses)-3, -1):
          if i < 0:
              break
          encoded_vector = tokenizer.encode(generated_responses[i] + tokenizer.eos_token, return_tensors='pt')
          if text_idx.shape[-1] + encoded_vector.shape[-1] < 1000:
              text_idx = torch.cat([encoded_vector, text_idx], dim=-1)
          else:
              break
          encoded_vector = tokenizer.encode(past_user_inputs[i] + tokenizer.eos_token, return_tensors='pt')
          if text_idx.shape[-1] + encoded_vector.shape[-1] < 1000:
              text_idx = torch.cat([encoded_vector, text_idx], dim=-1)
          else:
              break
      text_idx = text_idx.to(device)
      inference_output = model.generate(
              text_idx,
              max_length=1000,
              num_beams=5,
              top_k=20,
              no_repeat_ngram_size=4,
              length_penalty=0.65,
              repetition_penalty=2.0,
          )
      inference_output = inference_output.tolist()
      bot_response = tokenizer.decode(inference_output[0][text_idx.shape[-1]:], skip_special_tokens=True)
      print(f"Bot: {bot_response}")
      past_user_inputs.append(user_input)
      generated_responses.append(bot_response)
  ```
  
  ### Reference
  * [SKT-KoGPT2](https://huggingface.co/skt/kogpt2-base-v2)
  * [KETI R&D 데이터](https://aihub.or.kr/opendata/keti-data/recognition-laguage/KETI-02-008)
  * [한국어 대화 요약](https://aihub.or.kr/aidata/30714)
  