I'm just tinkering. All credit to the original creators: Noromaid is hot.
"rpcal" designates that this model was quantized using an RP-specific data set instead of the generalized wiki or llama data set. I have been unable to quantify real differences in the same model "compressed" using these two different methods. It "feels" better, but I can't put my finger on why. My current theory is that it gives "good responses" just as often as a similarly quantized model, however, good responses are "subjectively better" with this method. Any help quantifying this would be appreciated. Anyone know Ayumi?
This model: EXL2 @ 2.5 bpw using RP data for calibration.
Sadly, this one really seems to lose something essential compared to the 3.5 bpw version.
MiquMaid v3
Check out our blogpost about this model series Here! - Join our Discord server Here!
This model uses the Alpaca prompting format
Model trained for RP conversation on Miqu-70B with our magic sauce. Then we made an enormous merge containing all out old iteration of Miqumaid, and some other RP Miqu based model, with the new Model Stock merging method.
