readme: ---
  language:
  - en  # Example: fr
  tags:
  - conversational  # Example: audio
  - gpt2  # Example: automatic-speech-recognition
  datasets:
  - Discord transcripts 
  ---
  
  ### About NegaNetizen
  Trained on conversations from a friend for use within their discord server.
  
  ### How to use
  
  ```python
  
  from transformers import AutoModelForCausalLM, AutoTokenizer
  import torch
  
  tokenizer = AutoTokenizer.from_pretrained("microsoft/DialoGPT-medium")
  model = AutoModelForCausalLM.from_pretrained('jordanhagan/DialoGPT-medium-NegaNetizen')
  
  # Let's chat for 5 lines
  for step in range(5):
  
      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=200,
          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
      )
      
      # pretty print last ouput tokens from bot
      print("NNR: {}".format(tokenizer.decode(chat_history_ids[:, bot_input_ids.shape[-1]:][0], skip_special_tokens=True)))
  ```
  
  