HQQ Tracker

[HDCharles]

• A16W4 axis=1

  • Low hanging fruit we can add to int4wo quant as either a flag or replace the quant method
    • [x] test eval with HQQ axis=1 and compare to existing version
  • if axis = 1 doesn't get enough accuracy improvement, we could also combine with equalization
    • [x] test perf/eval with HQQ axis=1 + equalization

• A16W4+ axis=1

  • Can quantize certain columns of W to 4/8 bit
    • may be faster to do a 4 bit matmul on all of W and a sparse 8 bit matmul?
    • [ ] test perf for int4wo + int8 matmul for n columns
  • HQQ+ end result is an int4wo matmul + lora matmul
    • back of envelope numbers look like 1/3 slowdown over int4 which is still better than int8
    • [ ] test perf for int4wo + lora

• A8W4 axis=1

  • [ ] test eval accuracy with HQQ axis=1 and compare to existing version

• A16W3 and A16W5

  • existing numbers depend on axis = 0, how do these numbers look with axis = 1
    • also relevant whether these numbers scale to llama3 since some quantization difficulty has been reported there
  • [ ] get numbers for 3/5 bit quantization with axis = 1, ideally for llama 3

[mobicham]

@HDCharles Thanks! what do you mean by equalization ?