Is there somewhere more detailed insight on arguments and their influence on the output?

[mirozahorak]

Is there any more in depth info on how to adjust the arguments for best results? More specifically i mean these arguments, for us, who are not at home with ML, please?

  -mc N,     --max-context N     [-1     ] maximum number of text context tokens to store
  -ml N,     --max-len N         [0      ] maximum segment length in characters
  -bo N,     --best-of N         [5      ] number of best candidates to keep
  -bs N,     --beam-size N       [-1     ] beam size for beam search
  -wt N,     --word-thold N      [0.01   ] word timestamp probability threshold
  -et N,     --entropy-thold N   [2.40   ] entropy threshold for decoder fail
  -lpt N,    --logprob-thold N   [-1.00  ] log probability threshold for decoder fail
  -nf,       --no-fallback       [false  ] do not use temperature fallback while decoding

I was playing with some random adjustments but see no effect in the output.

[rianbrob]

found this

#291