readme: ---
  tags:
  - conversational
  language:
  - en
  ---
  
  # HomerBot: A conversational chatbot imitating Homer Simpson
  
  This model is a fine-tuned [DialoGPT](https://huggingface.co/microsoft/DialoGPT-medium) (medium version) on Simpsons [scripts](https://www.kaggle.com/datasets/pierremegret/dialogue-lines-of-the-simpsons).
  
  More specifically, we fine-tune DialoGPT-medium for 3 epochs on 10K **(character utterance, Homer's response)** pairs
  
  For more details, check out our git [repo](https://github.com/jesseDingley/HomerBot) containing all the code.  
  
  ### How to use
  
  
  ```python
  from transformers import AutoModelForCausalLM, AutoTokenizer
  import torch 
  
  tokenizer = AutoTokenizer.from_pretrained("DingleyMaillotUrgell/homer-bot")
  model = AutoModelForCausalLM.from_pretrained("DingleyMaillotUrgell/homer-bot")
  
  # 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,  
          no_repeat_ngram_size=3,
          do_sample=True, 
          top_k=100, 
          top_p=0.7,
          temperature = 0.8
      )
      
      # print last outpput tokens from bot
      print("Homer: {}".format(tokenizer.decode(chat_history_ids[:, bot_input_ids.shape[-1]:][0], skip_special_tokens=True)))
  ```
   