text: # Source: https://huggingface.co/microsoft/DialoGPT-medium
  
  from transformers import AutoModelForCausalLM, AutoTokenizer
  import torch
  
  
  #tokenizer = AutoTokenizer.from_pretrained("microsoft/DialoGPT-medium")
  #model = AutoModelForCausalLM.from_pretrained("microsoft/DialoGPT-medium")
  
  tokenizer = AutoTokenizer.from_pretrained("microsoft/DialoGPT-large")
  model = AutoModelForCausalLM.from_pretrained("microsoft/DialoGPT-large")
  
  
  chat_history_ids = []
  # Let's chat for 5 lines
  for step in range(5):
      # 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')
  
      # 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)
  
      # pretty print last ouput tokens from bot
      print("DialoGPT: {}".format(tokenizer.decode(chat_history_ids[:, bot_input_ids.shape[-1]:][0], skip_special_tokens=True)))
  