TOC_DISCORD_BOT

DiscordLLM

By using model quantization you can run larger llms on your device that was not possible prior. Learn more about hardware needed without model quantization here: https://www.hardware-corner.net/guides/computer-to-run-llama-ai-model/

This DiscordBot uses StableBeluga7B for this example and does not remember history as it is meant to be a one shot answer in whatever specialized prompt you would like. In the future history can be brought back or you could extend this yourself.

LEARNED about model quantization from sentdex(code is only on huggingface)

REF: https://huggingface.co/spaces/Sentdex/StableBeluga-7B-Chat/blob/main/app.py

HUGGING FACE OPEN SOURCE LLM LEADERBOARDS https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard

MODEL QUANTIZATION https://huggingface.co/docs/transformers/main_classes/quantization

TURN INTO A TERMINAL BOT

def main():
  print("\n\n  LLMAgents init()\n")

  _chain = Chain()
  isAsking = True
  # _chain.chat("What color is the sun?", _chain.PROMPTS[0])

  while(isAsking):
    _input = input(clr.bar + "\n  Want to know anything?\n :  " + clr.clear)
    if(_input == "no"):
      isAsking = False
      print(clr.bold + "\n  Bot is going back to hibernation." + clr.clear) 
      break
    
    _chain.chat(_input, _chain.PROMPTS[0])



if __name__ == "__main__":
  main()