This repository hosts quantized GGUF files for Loyal-Toppy-Bruins-Maid-7B, a 7B model aimed at having engaging RP with solid character card adherence and being a smart cookie at the same time.
The other foundational model is chargoddard/loyal-piano-m7, chosen for its strong RP performance and Alpaca format training, with a diverse dataset including PIPPA, rpbuild, and LimaRP.
Undi95/Toppy-M-7B, known for its creativity, brings in useful RP data from various sources. It ranks first among 7B models on OpenRouter for a good reason.
NeverSleep/Noromaid-7b-v0.1.1, a Mistral finetune with unique RP data not present in other models, was also added for bringing in a unique RP dataset and being a well-regarded RP model.
The models were merged using the DARE ties method, with a targeted 1.2 absolute weight and high density (0.5-0.6), as discussed in the MergeKit GitHub Repo.
Currently, this model ranks at the top of my personal RP unit test benchmark and scored a very solid 20 on lilblam's LLM Logic Test. My first impressions of it for RPing are very good but, admittedly, this model came out of the oven today so I haven't played it with it too much 😊
The sauce
models: # Top-Loyal-Bruins-Maid-DARE-7B_v2
- model: mistralai/Mistral-7B-v0.1
# no parameters necessary for base model
- model: rwitz/go-bruins-v2 # MetamathCybertronStarling base
parameters:
weight: 0.5
density: 0.6
- model: chargoddard/loyal-piano-m7 # Pull in some PIPPA/LimaRP/Orca/rpguild
parameters:
weight: 0.5
density: 0.6
- model: Undi95/Toppy-M-7B
parameters:
weight: 0.1
density: 0.5
- model: NeverSleep/Noromaid-7b-v0.1.1
parameters:
weight: 0.1
density: 0.5
merge_method: dare_ties
base_model: mistralai/Mistral-7B-v0.1
parameters:
normalize: false
int8_mask: true
dtype: bfloat16
Prompt template: Custom format, or Alpaca
Custom format:
I found the best SillyTavern results from using the Noromaid template.
