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FBI-LLM:

  • Columnwise scaling, learns alpha, beta linear scale + shift factors. Otherwise just signs the column weights, quite simple
  • Only teacher/student loss, cross entropy instead of KL. No CE term.
  • Use pretrained model as teacher (eg. Llama2-7B), also the full-precision version of student like in FBI LLM.
  • Found that training from scratch was more suited to 1B than pretrained LLm weight (seems consistent with bitnet)
  • Is essentially training from scratch, even with distillation. Uses pajama dataset, massive number of tokens.