readme: ---
  language:
  - en
  metrics:
  - accuracy
  co2_eq_emissions:
        emissions: "10"
        source: "mlco2.github.io"
        training_type: "fine-tuning"
        geographical_location: "West Java, Indonesia"
        hardware_used: "1 T4"
  license: cc-by-nc-sa-4.0
  widget:
  - text: 'You: "Hey kekbot! Whats up?"\nKekbot: "'
    example_title: "Asking what's up"
  - text: 'You: "Hey kekbot! How r u?"\nKekbot: "'
    example_title: "Asking how he is"
  ---
  > THIS MODEL IS INTENDED FOR RESEARCH PURPOSES ONLY
  # Kekbot Mini
  
  Based on a `distilgpt2` model, fine-tuned to a select subset (65k<= messages) of Art Union's general-chat channel chat history.
  
  ### Limits and biases
  As this is trained on chat history, it is possible that discriminatory or even offensive materials to be outputted. 
  Author holds his ground on the fact that ML models are mere statistical representation of the dataset used to train it, 
  and that due to the nature of the dataset it is practically impossible to be certain of 
  the degree of "cleanliness" that the data contained within holds.
  
  Author can confirm, however, that from heuristical testing that the model was not found to be offensive 
  to the author himself, hopefully this opinion stays true for everyone in the audience.
  