---
language:
- en
license: apache-2.0
tags:
- dare
- super mario merge
- pytorch
- mixtral
- merge
pipeline_tag: text-generation
inference: false
model-index:
- name: mixtral-megamerge-dare-8x7b-v2
  results:
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: AI2 Reasoning Challenge (25-Shot)
      type: ai2_arc
      config: ARC-Challenge
      split: test
      args:
        num_few_shot: 25
    metrics:
    - type: acc_norm
      value: 66.47
      name: normalized accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=martyn/mixtral-megamerge-dare-8x7b-v2
      name: Open LLM Leaderboard
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: HellaSwag (10-Shot)
      type: hellaswag
      split: validation
      args:
        num_few_shot: 10
    metrics:
    - type: acc_norm
      value: 86.11
      name: normalized accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=martyn/mixtral-megamerge-dare-8x7b-v2
      name: Open LLM Leaderboard
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: MMLU (5-Shot)
      type: cais/mmlu
      config: all
      split: test
      args:
        num_few_shot: 5
    metrics:
    - type: acc
      value: 69.14
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=martyn/mixtral-megamerge-dare-8x7b-v2
      name: Open LLM Leaderboard
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: TruthfulQA (0-shot)
      type: truthful_qa
      config: multiple_choice
      split: validation
      args:
        num_few_shot: 0
    metrics:
    - type: mc2
      value: 53.81
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=martyn/mixtral-megamerge-dare-8x7b-v2
      name: Open LLM Leaderboard
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: Winogrande (5-shot)
      type: winogrande
      config: winogrande_xl
      split: validation
      args:
        num_few_shot: 5
    metrics:
    - type: acc
      value: 79.79
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=martyn/mixtral-megamerge-dare-8x7b-v2
      name: Open LLM Leaderboard
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: GSM8k (5-shot)
      type: gsm8k
      config: main
      split: test
      args:
        num_few_shot: 5
    metrics:
    - type: acc
      value: 53.9
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=martyn/mixtral-megamerge-dare-8x7b-v2
      name: Open LLM Leaderboard
---

# mixtral megamerge 8x7b v2

The following models were merged with DARE using [https://github.com/martyn/safetensors-merge-supermario](https://github.com/martyn/safetensors-merge-supermario)

## Mergelist

```
mistralai/Mixtral-8x7B-v0.1
mistralai/Mixtral-8x7B-Instruct-v0.1
cognitivecomputations/dolphin-2.6-mixtral-8x7b
Brillibitg/Instruct_Mixtral-8x7B-v0.1_Dolly15K
orangetin/OpenHermes-Mixtral-8x7B
NeverSleep/Noromaid-v0.1-mixtral-8x7b-v3
```

## Merge command

```
python3 hf_merge.py to_merge_mixtral2.txt mixtral-2 -p 0.15 -lambda 1.95
```

### Notes

* MoE gates were filtered for compatibility then averaged with `(tensor1 + tensor2)/2`
* seems to generalize prompting formats and sampling settings

# [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)
Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_martyn__mixtral-megamerge-dare-8x7b-v2)

|             Metric              |Value|
|---------------------------------|----:|
|Avg.                             |68.20|
|AI2 Reasoning Challenge (25-Shot)|66.47|
|HellaSwag (10-Shot)              |86.11|
|MMLU (5-Shot)                    |69.14|
|TruthfulQA (0-shot)              |53.81|
|Winogrande (5-shot)              |79.79|
|GSM8k (5-shot)                   |53.90|