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---
license: apache-2.0
library_name: transformers
tags:
- mergekit
- merge
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
inference: false
model-index:
- name: Moza-7B-v1.0
  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: 66.55
      name: normalized accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=kidyu/Moza-7B-v1.0
      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: 83.45
      name: normalized accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=kidyu/Moza-7B-v1.0
      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: 62.77
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=kidyu/Moza-7B-v1.0
      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: 65.16
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=kidyu/Moza-7B-v1.0
      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: 77.51
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=kidyu/Moza-7B-v1.0
      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: 62.55
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=kidyu/Moza-7B-v1.0
      name: Open LLM Leaderboard
---
# Moza-7B-v1.0

![image/png](https://cdn-uploads.huggingface.co/production/uploads/63474d73511cd17d2c790ed7/e7hw2xIzfpUseCFEOINg7.png)

This is a [meme-merge](https://en.wikipedia.org/wiki/Joke) of pre-trained language models,
created using [mergekit](https://github.com/cg123/mergekit).
Use at your own risk.

## Details
### Quantized Model
- [GGUF](https://huggingface.co/kidyu/Moza-7B-v1.0-GGUF)

### Merge Method

This model was merged using the [DARE](https://arxiv.org/abs/2311.03099) [TIES](https://arxiv.org/abs/2306.01708) merge method,
using [mistralai/Mistral-7B-v0.1](https://huggingface.co/mistralai/Mistral-7B-v0.1) as a base.

The value for `density` are from [this blogpost](https://huggingface.co/blog/mlabonne/merge-models),
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](https://huggingface.co/cognitivecomputations/dolphin-2.2.1-mistral-7b)
* [Open-Orca/Mistral-7B-OpenOrca](https://huggingface.co/Open-Orca/Mistral-7B-OpenOrca)
* [openchat/openchat-3.5-0106](https://huggingface.co/openchat/openchat-3.5-0106)
* [mlabonne/NeuralHermes-2.5-Mistral-7B](https://huggingface.co/mlabonne/NeuralHermes-2.5-Mistral-7B)
* [GreenNode/GreenNode-mini-7B-multilingual-v1olet](https://huggingface.co/GreenNode/GreenNode-mini-7B-multilingual-v1olet)
* [berkeley-nest/Starling-LM-7B-alpha](https://huggingface.co/berkeley-nest/Starling-LM-7B-alpha)
* [viethq188/LeoScorpius-7B-Chat-DPO](https://huggingface.co/viethq188/LeoScorpius-7B-Chat-DPO)
* [meta-math/MetaMath-Mistral-7B](https://huggingface.co/meta-math/MetaMath-Mistral-7B)
* [Intel/neural-chat-7b-v3-3](https://huggingface.co/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:

```yaml
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
```
# [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_kidyu__Moza-7B-v1.0)

|             Metric              |Value|
|---------------------------------|----:|
|Avg.                             |69.66|
|AI2 Reasoning Challenge (25-Shot)|66.55|
|HellaSwag (10-Shot)              |83.45|
|MMLU (5-Shot)                    |62.77|
|TruthfulQA (0-shot)              |65.16|
|Winogrande (5-shot)              |77.51|
|GSM8k (5-shot)                   |62.55|