Update 2023-12-19
In light of dataset contamination issue among the merged models raised by the community in recent days, in particular berkeley-nest/Starling-LM-7B-alpha, and Q-bert/MetaMath-Cybertron-Starling, we decided to remake another model without the models mentioned. Additionally, their CC-by-NC-4.0 license is restrictive and thus are not suitable for an open model.
Model Description
This is an experiment to test merging 14 models using DARE TIES ๐ฆ
The result is a base model that performs quite well but requires some further instruction fine-tuning.
The 14 models are as follows:
- mistralai/Mistral-7B-Instruct-v0.2
- ehartford/dolphin-2.2.1-mistral-7b
- SciPhi/SciPhi-Mistral-7B-32k
- ehartford/samantha-1.2-mistral-7b
- Arc53/docsgpt-7b-mistral
- berkeley-nest/Starling-LM-7B-alpha
- Q-bert/MetaMath-Cybertron-Starling
- Open-Orca/Mistral-7B-OpenOrca
- v1olet/v1olet_marcoroni-go-bruins-merge-7B
- beowolx/MistralHermes-CodePro-7B-v1
- TIGER-Lab/MAmmoTH-7B-Mistral
- teknium/OpenHermes-2.5-Mistral-7B
- Weyaxi/OpenHermes-2.5-neural-chat-v3-3-Slerp
- mlabonne/NeuralHermes-2.5-Mistral-7B
- base model: mistralai/Mistral-7B-v0.1
The yaml config file for this model is here:
models:
- model: mistralai/Mistral-7B-v0.1
# no parameters necessary for base model
- model: ehartford/dolphin-2.2.1-mistral-7b
parameters:
weight: 0.08
density: 0.4
- model: SciPhi/SciPhi-Mistral-7B-32k
parameters:
weight: 0.08
density: 0.4
- model: ehartford/samantha-1.2-mistral-7b
parameters:
weight: 0.08
density: 0.4
- model: Arc53/docsgpt-7b-mistral
parameters:
weight: 0.08
density: 0.4
- model: berkeley-nest/Starling-LM-7B-alpha
parameters:
weight: 0.08
density: 0.4
- model: Q-bert/MetaMath-Cybertron-Starling
parameters:
weight: 0.08
density: 0.4
- model: Open-Orca/Mistral-7B-OpenOrca
parameters:
weight: 0.08
density: 0.4
- model: v1olet/v1olet_marcoroni-go-bruins-merge-7B
parameters:
weight: 0.08
density: 0.4
- model: beowolx/MistralHermes-CodePro-7B-v1
parameters:
weight: 0.08
density: 0.4
- model: TIGER-Lab/MAmmoTH-7B-Mistral
parameters:
weight: 0.08
density: 0.4
- model: teknium/OpenHermes-2.5-Mistral-7B
parameters:
weight: 0.08
density: 0.4
- model: Weyaxi/OpenHermes-2.5-neural-chat-v3-3-Slerp
parameters:
weight: 0.08
density: 0.4
- model: mlabonne/NeuralHermes-2.5-Mistral-7B
parameters:
weight: 0.08
density: 0.4
- model: mistralai/Mistral-7B-Instruct-v0.2
parameters:
weight: 0.08
density: 0.5
merge_method: dare_ties
base_model: mistralai/Mistral-7B-v0.1
parameters:
int8_mask: true
dtype: bfloat16
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