metadata
base_model:
- mistralai/Mistral-7B-v0.1
- cognitivecomputations/dolphin-2.2.1-mistral-7b
- Open-Orca/Mistral-7B-OpenOrca
- openchat/openchat-3.5-0106
- mlabonne/NeuralHermes-2.5-Mistral-7B
- GreenNode/GreenNode-mini-7B-multilingual-v1olet
- berkeley-nest/Starling-LM-7B-alpha
- viethq188/LeoScorpius-7B-Chat-DPO
- meta-math/MetaMath-Mistral-7B
- Intel/neural-chat-7b-v3-3
library_name: transformers
inference: false
tags:
- mergekit
- merge
license: apache-2.0
Moza-7B-v1.0
This is a meme-merge of pre-trained language models, created using mergekit. Use at your own risk.
Details
Quantized Model
Merge Method
This model was merged using the DARE TIES merge method, using mistralai/Mistral-7B-v0.1 as a base.
The value for density
are from this blogpost,
and the weight was randomly generated and then assigned to the models,
with priority (of using the bigger weight) to NeuralHermes
, OpenOrca
, and neural-chat
.
The models themselves are chosen by "vibes".
Models Merged
The following models were included in the merge:
- cognitivecomputations/dolphin-2.2.1-mistral-7b
- Open-Orca/Mistral-7B-OpenOrca
- openchat/openchat-3.5-0106
- mlabonne/NeuralHermes-2.5-Mistral-7B
- GreenNode/GreenNode-mini-7B-multilingual-v1olet
- berkeley-nest/Starling-LM-7B-alpha
- viethq188/LeoScorpius-7B-Chat-DPO
- meta-math/MetaMath-Mistral-7B
- Intel/neural-chat-7b-v3-3
Prompt Format
You can use Alpaca
formatting for inference
### Instruction:
### Response:
Configuration
The following YAML configuration was used to produce this model:
base_model: mistralai/Mistral-7B-v0.1
models:
- model: mlabonne/NeuralHermes-2.5-Mistral-7B
parameters:
density: 0.63
weight: 0.83
- model: Intel/neural-chat-7b-v3-3
parameters:
density: 0.63
weight: 0.74
- model: meta-math/MetaMath-Mistral-7B
parameters:
density: 0.63
weight: 0.22
- model: openchat/openchat-3.5-0106
parameters:
density: 0.63
weight: 0.37
- model: Open-Orca/Mistral-7B-OpenOrca
parameters:
density: 0.63
weight: 0.76
- model: cognitivecomputations/dolphin-2.2.1-mistral-7b
parameters:
density: 0.63
weight: 0.69
- model: viethq188/LeoScorpius-7B-Chat-DPO
parameters:
density: 0.63
weight: 0.38
- model: GreenNode/GreenNode-mini-7B-multilingual-v1olet
parameters:
density: 0.63
weight: 0.13
- model: berkeley-nest/Starling-LM-7B-alpha
parameters:
density: 0.63
weight: 0.33
merge_method: dare_ties
parameters:
normalize: true
int8_mask: true
dtype: bfloat16