library_name: transformers
tags:
- mistral
- quantized
- text-generation-inference
- merge
pipeline_tag: text-generation
inference: false
license: cc-by-nc-4.0
[Quantizing and uploading...]
GGUF-Imatrix quantizations for SanjiWatsuki/Loyal-Toppy-Bruins-Maid-7B-DARE.
The new IQ3_S quant-option has shown to be better than the old Q3_K_S, so I added that instead of the later. Only supported in koboldcpp-1.59.1 or higher.
If you want any specific quantization to be added, feel free to ask.
All credits belong to the creator.
Base⇢ GGUF(F16)⇢ Imatrix-Data(F16)⇢ GGUF(Imatrix-Quants)
For --imatrix data, imatrix-Loyal-Toppy-Bruins-Maid-7B-DARE-F16.dat was used.
Original model information:
Description
This repository hosts FP16 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 😊
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: