readme: ---
  
  language:
  - en
  tags:
  - text-generation
  - gpt2
  - gpt
  license: mit
  datasets:
  - natural questions
  
  widget:
  - text: "hi, how are you doing bruh?\nperson beta:\n\n"
    example_title: "greeting"
  - text: "Can you actually take me for dinner somewhere nice this time?\nperson beta:\n\n"
    example_title: "dinner"
  - text: "Honey, I have clogged the toilet for the third time this month.. sorry..\nperson beta:\n\n"
    example_title: "overflow"
  - text: "A man pushes his car to a hotel and tells the owner he’s bankrupt. Why?\nperson beta:\n\n"
    example_title: "brain teaser"
  
  inference:
    parameters:
      min_length: 2
      max_length: 64
      length_penalty: 0.7
      no_repeat_ngram_size: 3
      do_sample: True
      top_p: 0.85
      top_k: 10
      repetition_penalty: 2.1
      
  
  ---
  
  # GPT-Neo 1.3 B Conversational - 17 total epochs
  
  - trained on the Wizard of Wikipedia parl.ai dataset + Daily Dialogues dataset
    - 13 on WoW 4 on Daily Dialogues
  - the aim is to use the model as a customizable chatbot with the personID labels as pseudo-SOT/EOT tokens, i.e. ending the prompt with `person beta:` means that it is extremely likely that _person beta:_ responds, as opposed to the entered prompt being added on to.
  - a link to the project repo that details how to effectively use such a trained model is [here](https://github.com/pszemraj/ai-msgbot)