readme: ---
  tags:
  - conversational
  ---
  
  # Let's chat for 4 line
      # encode the new user input, add the eos_token and return a tensor in Pytorch
  new_user_input_ids = tokenizer.encode(input(">> User:") + tokenizer.eos_token, return_tensors='pt')
      # print(new_user_input_ids)
  
      # append the new user input tokens to the chat history
  bot_input_ids = torch.cat([chat_history_ids, new_user_input_ids], dim=-1) if step > 0 else new_user_input_ids
  
      # generated a response while limiting the total chat history to 1000 tokens, 
  chat_history_ids = model.generate(bot_input_ids, max_length=1000, pad_token_id=tokenizer.eos_token_id, temperature=0.6, repetition_penalty=1.3)
  
      
      # pretty print last ouput tokens from bot
  #    print("Endella: {}".format(tokenizer.decode(chat_history_ids[:, bot_input_ids.shape[-1]:][0], skip_special_tokens=True)))
  # Endella DialoGPT Model