MN-Violet-Lotus-12B

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!

GGUF Quants:

• https://huggingface.co/backyardai/MN-Violet-Lotus-12B-GGUF
• https://huggingface.co/mradermacher/MN-Violet-Lotus-12B-GGUF
• https://huggingface.co/mradermacher/MN-Violet-Lotus-12B-i1-GGUF

Recommended ST Settings

Special thanks to @Zeldazachman for these amazing ST settings that I now wholeheartedly recommend!

Merge Details

This is a merge of pre-trained language models created using mergekit.

Merge Method

This model was merged using the Model Stock merge method.

Models Merged

The following models were included in the merge:

• Epiculous/Violet_Twilight-v0.2
• NeverSleep/Lumimaid-v0.2-12B
• flammenai/Mahou-1.5-mistral-nemo-12B
• Sao10K/MN-12B-Lyra-v4

Configuration

The following YAML configuration was used to produce this model:

models:
  - model: FallenMerick/MN-Twilight-Maid-SLERP-12B #(unreleased)
  - model: Sao10K/MN-12B-Lyra-v4
  - model: flammenai/Mahou-1.5-mistral-nemo-12B
merge_method: model_stock
base_model: mistralai/Mistral-Nemo-Instruct-2407
parameters:
  normalize: true
dtype: 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.