
# Update 2024-01-03

Check out our [v0.4 model](https://huggingface.co/EmbeddedLLM/Mistral-7B-Merge-14-v0.4) which is based on this and achieves better average score of 71.19 versus 69.66.

# Model Description

This is an update to [EmbeddedLLM/Mistral-7B-Merge-14-v0.2](https://huggingface.co/EmbeddedLLM/Mistral-7B-Merge-14-v0.2) that removes
potentially TruthfulQA-contaminated models and non-commercially licensed models:
1. [berkeley-nest/Starling-LM-7B-alpha](https://huggingface.co/berkeley-nest/Starling-LM-7B-alpha)
2. [Q-bert/MetaMath-Cybertron-Starling](https://huggingface.co/Q-bert/MetaMath-Cybertron-Starling)
3. [v1olet/v1olet_marcoroni-go-bruins-merge-7B](https://huggingface.co/v1olet/v1olet_marcoroni-go-bruins-merge-7B)


This is an experiment to test merging 14 models using DARE TIES 🦙

The result is a base model that performs quite well but may need some further chat 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. [HuggingFaceH4/zephyr-7b-beta](https://huggingface.co/HuggingFaceH4/zephyr-7b-beta)
7. [meta-math/MetaMath-Mistral-7B](https://huggingface.co/meta-math/MetaMath-Mistral-7B)
8. [Open-Orca/Mistral-7B-OpenOrca](https://huggingface.co/Open-Orca/Mistral-7B-OpenOrca)
9. [openchat/openchat-3.5-1210](https://huggingface.co/openchat/openchat-3.5-1210)
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)

## Open LLM Leaderboard

|            | v0.3  | v0.4  |
|------------|-------|-------|
| Average    | 69.66 | 71.19 |
| ARC        | 65.96 | 66.81 |
| HellaSwag  | 85.29 | 86.15 |
| MMLU       | 64.35 | 65.10 |
| TruthfulQA | 57.80 | 58.25 |
| Winogrande | 78.30 | 80.03 |
| GSM8K      | 66.26 | 70.81 |

## Chat Template

We tried ChatML and Llama-2 chat template, but feel free to try other templates.

## Merge Configuration

The merge 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: HuggingFaceH4/zephyr-7b-beta
    parameters:
      weight: 0.08
      density: 0.4
  - model: meta-math/MetaMath-Mistral-7B
    parameters:
      weight: 0.08
      density: 0.4
  - model: Open-Orca/Mistral-7B-OpenOrca
    parameters:
      weight: 0.08
      density: 0.4
  - model: openchat/openchat-3.5-1210
    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

```
{"language": ["en"], "license": "apache-2.0", "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", "HuggingFaceH4/zephyr-7b-beta", "meta-math/MetaMath-Mistral-7B", "Open-Orca/Mistral-7B-OpenOrca", "openchat/openchat-3.5-1210", "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"]}
transformers pytorch safetensors mistral text-generation merge en base_model:mistralai/Mistral-7B-Instruct-v0.2 base_model:ehartford/dolphin-2.2.1-mistral-7b base_model:SciPhi/SciPhi-Mistral-7B-32k base_model:ehartford/samantha-1.2-mistral-7b base_model:Arc53/docsgpt-7b-mistral base_model:HuggingFaceH4/zephyr-7b-beta base_model:meta-math/MetaMath-Mistral-7B base_model:Open-Orca/Mistral-7B-OpenOrca base_model:openchat/openchat-3.5-1210 base_model:beowolx/MistralHermes-CodePro-7B-v1 base_model:TIGER-Lab/MAmmoTH-7B-Mistral base_model:teknium/OpenHermes-2.5-Mistral-7B base_model:Weyaxi/OpenHermes-2.5-neural-chat-v3-3-Slerp base_model:mlabonne/NeuralHermes-2.5-Mistral-7B license:apache-2.0 autotrain_compatible endpoints_compatible text-generation-inference region:us