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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
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|
|