readme: ---
  tags:
  - conversational
  ---
  
  ```python
  from transformers import AutoTokenizer, AutoModelWithLMHead
    
  tokenizer = AutoTokenizer.from_pretrained("UmUDev/DialoGPT-medium-Alex")
  
  model = AutoModelWithLMHead.from_pretrained("UmUDev/DialoGPT-medium-Alex")
  
  
  print("====chatting 5 times with nucleus & top-k sampling & tweaking temperature & multiple sentences====")
  # chatting 5 times with nucleus & top-k sampling & tweaking temperature & multiple
  # sentences
  for step in range(20):
      # take user input
      text = input(">> You:")
      # encode the input and add end of string token
      input_ids = tokenizer.encode(text + tokenizer.eos_token, return_tensors="pt")
      # concatenate new user input with chat history (if there is)
      bot_input_ids = torch.cat([chat_history_ids, input_ids], dim=-1) if step > 0 else input_ids
      # generate a bot response
      chat_history_ids_list = model.generate(
          bot_input_ids,
          max_length=1000,
          do_sample=True,
          top_p=0.95,
          top_k=50,
          temperature=0.75,
          num_return_sequences=5,
          pad_token_id=tokenizer.eos_token_id
      )
      #print the outputs
      for i in range(len(chat_history_ids_list)):
        output = tokenizer.decode(chat_history_ids_list[i][bot_input_ids.shape[-1]:], skip_special_tokens=True)
        print(f"DialoGPT {i}: {output}")
      choice_index = int(input("Choose the response you want for the next input: "))
      chat_history_ids = torch.unsqueeze(chat_history_ids_list[choice_index], dim=0)
  ```