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Description

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.

Its foundation is Starling-LM-7B-alpha, notable for its performance in the LMSYS Chatbot Arena, even surpassing GPT-3.5-Turbo-1106. The model incorporates rwitz/go-bruins-v2, a Q-bert/MetaMath-Cybertron-Starling derivative with Alpaca RP data tuning.

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 ๐Ÿ˜Š

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.

SillyTavern config files: Context, Instruct.

Otherwise, I tried to ensure that all of the underlying merged models were Alpaca favored.

Alpaca:

Below is an instruction that describes a task. Write a response that appropriately completes the request.

### Instruction:
{prompt}

### Response:
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llama

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Inference API
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