This is quantized version of
FallenMerick/MN-Violet-Lotus-12B created using llama.cpp
This is the model I was trying to create when
Chunky-Lotus emerged. Not only does this model score higher on my local EQ benchmarks (80.00 w/ 100% parsed @ 8-bit), but it does an even better job at roleplaying and producing creative outputs while still adhering to wide ranges of character personalities. The high levels of emotional intelligence are really quite noticeable as well.
Once again, models tend to score higher on my local tests when compared to their posted scores, but this has become the new high score for models I've personally tested.
I really like the way this model writes, and I hope you'll enjoy using it as well!
Special thanks to
@Zeldazachman for these amazing ST settings that I now wholeheartedly recommend!
This is a merge of pre-trained language models created using
mergekit.
This model was merged using the
Model Stock merge method.
1models:
2 - model: FallenMerick/MN-Twilight-Maid-SLERP-12B #(unreleased)
3 - model: Sao10K/MN-12B-Lyra-v4
4 - model: flammenai/Mahou-1.5-mistral-nemo-12B
5merge_method: model_stock
6base_model: mistralai/Mistral-Nemo-Instruct-2407
7parameters:
8 normalize: true
9dtype: bfloat16
In this recipe, Violet Twilight and Lumimaid were first blended using the SLERP method to create a strong roleplaying foundation. Lyra v4 is then added to the mix for its great creativity and roleplaying performance, along with Mahou to once again curtail the outputs and prevent the resulting model from becoming too wordy. Model Stock was used for the final merge in order to really push the resulting weights in the proper direction while using Nemo Instruct as a strong anchor point.