I recently ran into this quantized model of Noromaid with the "rpcal" term on the end.
The secret sauce used an RP data set instead of the standard llama dataset to do the quantizing.
On a test drive, this seemed to make an enormous difference in the quality of the output, but I'm going to make a couple of my own to compare results.

EXL2 @ 4.00bpw
All credit to the original creators: Noromaid is hot.

This model uses the Chatml prompting format

Beeg noromaid on steroids. Suitable for RP, ERP.

This model was trained on the Zloss fork of Charles, and should fix issue the model had.

Use Chatml prompt format, but not the special token.

The reason is that Axolotl merge the finetune with the base model at 1.0 weight basically, but this is too much, so I use another script available HERE to merge with less weight, sadly, it don't take the special Chatml token. It's like Orca2 for the matter.

This repo contains FP16 files of Noromaid-v0.4-Mixtral-Instruct-8x7b-Zloss.

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<|im_start|>system
{sysprompt}<|im_end|>
<|im_start|>user
{input}<|im_end|>
<|im_start|>assistant
{output}<|im_end|>

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