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license: cc-by-nc-4.0
language:
- en
tags:
- merge
base_model:
- 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
---
# Update 2023-12-19
In light of [dataset contamination issue among the merged models](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard/discussions/474)
raised by the community in recent days, in particular
[berkeley-nest/Starling-LM-7B-alpha](https://huggingface.co/berkeley-nest/Starling-LM-7B-alpha), and
[Q-bert/MetaMath-Cybertron-Starling](https://huggingface.co/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 🦙
The result is a base model that performs quite well but requires some further instruction fine-tuning.
The 14 models are as follows:
1. [mistralai/Mistral-7B-Instruct-v0.2](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.2)
2. [ehartford/dolphin-2.2.1-mistral-7b](https://huggingface.co/ehartford/dolphin-2.2.1-mistral-7b)
3. [SciPhi/SciPhi-Mistral-7B-32k](https://huggingface.co/SciPhi/SciPhi-Mistral-7B-32k)
4. [ehartford/samantha-1.2-mistral-7b](https://huggingface.co/ehartford/samantha-1.2-mistral-7b)
5. [Arc53/docsgpt-7b-mistral](https://huggingface.co/Arc53/docsgpt-7b-mistral)
6. [berkeley-nest/Starling-LM-7B-alpha](https://huggingface.co/berkeley-nest/Starling-LM-7B-alpha)
7. [Q-bert/MetaMath-Cybertron-Starling](https://huggingface.co/Q-bert/MetaMath-Cybertron-Starling)
8. [Open-Orca/Mistral-7B-OpenOrca](https://huggingface.co/Open-Orca/Mistral-7B-OpenOrca)
9. [v1olet/v1olet_marcoroni-go-bruins-merge-7B](https://huggingface.co/v1olet/v1olet_marcoroni-go-bruins-merge-7B)
10. [beowolx/MistralHermes-CodePro-7B-v1](https://huggingface.co/beowolx/MistralHermes-CodePro-7B-v1)
11. [TIGER-Lab/MAmmoTH-7B-Mistral](https://huggingface.co/TIGER-Lab/MAmmoTH-7B-Mistral)
12. [teknium/OpenHermes-2.5-Mistral-7B](https://huggingface.co/teknium/OpenHermes-2.5-Mistral-7B)
13. [Weyaxi/OpenHermes-2.5-neural-chat-v3-3-Slerp](https://huggingface.co/Weyaxi/OpenHermes-2.5-neural-chat-v3-3-Slerp)
14. [mlabonne/NeuralHermes-2.5-Mistral-7B](https://huggingface.co/mlabonne/NeuralHermes-2.5-Mistral-7B)
- base model: [mistralai/Mistral-7B-v0.1](https://huggingface.co/mistralai/Mistral-7B-v0.1)
The yaml config file for this model is here:
```yaml
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
``` |