初始化项目，由ModelHub XC社区提供模型
Model: kidyu/Moza-7B-v1.0 Source: Original Platform
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ModelHub XC
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README.md
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README.md
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---
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license: apache-2.0
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library_name: transformers
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tags:
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- mergekit
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- merge
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base_model:
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- mistralai/Mistral-7B-v0.1
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- cognitivecomputations/dolphin-2.2.1-mistral-7b
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- Open-Orca/Mistral-7B-OpenOrca
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- openchat/openchat-3.5-0106
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- mlabonne/NeuralHermes-2.5-Mistral-7B
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- GreenNode/GreenNode-mini-7B-multilingual-v1olet
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- berkeley-nest/Starling-LM-7B-alpha
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- viethq188/LeoScorpius-7B-Chat-DPO
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- meta-math/MetaMath-Mistral-7B
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- Intel/neural-chat-7b-v3-3
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inference: false
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model-index:
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- name: Moza-7B-v1.0
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results:
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- task:
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type: text-generation
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name: Text Generation
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dataset:
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name: AI2 Reasoning Challenge (25-Shot)
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type: ai2_arc
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config: ARC-Challenge
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split: test
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args:
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num_few_shot: 25
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metrics:
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- type: acc_norm
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value: 66.55
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name: normalized accuracy
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source:
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=kidyu/Moza-7B-v1.0
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name: Open LLM Leaderboard
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- task:
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type: text-generation
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name: Text Generation
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dataset:
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name: HellaSwag (10-Shot)
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type: hellaswag
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split: validation
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args:
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num_few_shot: 10
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metrics:
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- type: acc_norm
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value: 83.45
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name: normalized accuracy
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source:
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=kidyu/Moza-7B-v1.0
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name: Open LLM Leaderboard
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- task:
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type: text-generation
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name: Text Generation
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dataset:
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name: MMLU (5-Shot)
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type: cais/mmlu
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config: all
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split: test
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args:
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num_few_shot: 5
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metrics:
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- type: acc
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value: 62.77
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name: accuracy
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source:
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=kidyu/Moza-7B-v1.0
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name: Open LLM Leaderboard
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- task:
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type: text-generation
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name: Text Generation
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dataset:
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name: TruthfulQA (0-shot)
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type: truthful_qa
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config: multiple_choice
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split: validation
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args:
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num_few_shot: 0
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metrics:
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- type: mc2
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value: 65.16
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source:
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=kidyu/Moza-7B-v1.0
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name: Open LLM Leaderboard
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- task:
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type: text-generation
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name: Text Generation
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dataset:
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name: Winogrande (5-shot)
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type: winogrande
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config: winogrande_xl
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split: validation
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args:
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num_few_shot: 5
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metrics:
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- type: acc
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value: 77.51
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name: accuracy
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source:
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=kidyu/Moza-7B-v1.0
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name: Open LLM Leaderboard
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- task:
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type: text-generation
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name: Text Generation
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dataset:
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name: GSM8k (5-shot)
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type: gsm8k
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config: main
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split: test
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args:
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num_few_shot: 5
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metrics:
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- type: acc
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value: 62.55
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name: accuracy
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source:
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=kidyu/Moza-7B-v1.0
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name: Open LLM Leaderboard
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---
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# Moza-7B-v1.0
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This is a [meme-merge](https://en.wikipedia.org/wiki/Joke) of pre-trained language models,
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created using [mergekit](https://github.com/cg123/mergekit).
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Use at your own risk.
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## Details
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### Quantized Model
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- [GGUF](https://huggingface.co/kidyu/Moza-7B-v1.0-GGUF)
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### Merge Method
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This model was merged using the [DARE](https://arxiv.org/abs/2311.03099) [TIES](https://arxiv.org/abs/2306.01708) merge method,
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using [mistralai/Mistral-7B-v0.1](https://huggingface.co/mistralai/Mistral-7B-v0.1) as a base.
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The value for `density` are from [this blogpost](https://huggingface.co/blog/mlabonne/merge-models),
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and the weight was randomly generated and then assigned to the models,
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with priority (of using the bigger weight) to `NeuralHermes`, `OpenOrca`, and `neural-chat`.
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The models themselves are chosen by "vibes".
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### Models Merged
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The following models were included in the merge:
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* [cognitivecomputations/dolphin-2.2.1-mistral-7b](https://huggingface.co/cognitivecomputations/dolphin-2.2.1-mistral-7b)
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* [Open-Orca/Mistral-7B-OpenOrca](https://huggingface.co/Open-Orca/Mistral-7B-OpenOrca)
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* [openchat/openchat-3.5-0106](https://huggingface.co/openchat/openchat-3.5-0106)
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* [mlabonne/NeuralHermes-2.5-Mistral-7B](https://huggingface.co/mlabonne/NeuralHermes-2.5-Mistral-7B)
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* [GreenNode/GreenNode-mini-7B-multilingual-v1olet](https://huggingface.co/GreenNode/GreenNode-mini-7B-multilingual-v1olet)
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* [berkeley-nest/Starling-LM-7B-alpha](https://huggingface.co/berkeley-nest/Starling-LM-7B-alpha)
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* [viethq188/LeoScorpius-7B-Chat-DPO](https://huggingface.co/viethq188/LeoScorpius-7B-Chat-DPO)
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* [meta-math/MetaMath-Mistral-7B](https://huggingface.co/meta-math/MetaMath-Mistral-7B)
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* [Intel/neural-chat-7b-v3-3](https://huggingface.co/Intel/neural-chat-7b-v3-3)
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### Prompt Format
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You can use `Alpaca` formatting for inference
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```
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### Instruction:
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### Response:
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```
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### Configuration
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The following YAML configuration was used to produce this model:
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```yaml
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base_model: mistralai/Mistral-7B-v0.1
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models:
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- model: mlabonne/NeuralHermes-2.5-Mistral-7B
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parameters:
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density: 0.63
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weight: 0.83
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- model: Intel/neural-chat-7b-v3-3
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parameters:
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density: 0.63
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weight: 0.74
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- model: meta-math/MetaMath-Mistral-7B
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parameters:
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density: 0.63
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weight: 0.22
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- model: openchat/openchat-3.5-0106
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parameters:
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density: 0.63
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weight: 0.37
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- model: Open-Orca/Mistral-7B-OpenOrca
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parameters:
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density: 0.63
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weight: 0.76
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- model: cognitivecomputations/dolphin-2.2.1-mistral-7b
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parameters:
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density: 0.63
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weight: 0.69
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- model: viethq188/LeoScorpius-7B-Chat-DPO
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parameters:
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density: 0.63
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weight: 0.38
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- model: GreenNode/GreenNode-mini-7B-multilingual-v1olet
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parameters:
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density: 0.63
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weight: 0.13
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- model: berkeley-nest/Starling-LM-7B-alpha
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parameters:
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density: 0.63
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weight: 0.33
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merge_method: dare_ties
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parameters:
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normalize: true
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int8_mask: true
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dtype: bfloat16
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```
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# [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)
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Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_kidyu__Moza-7B-v1.0)
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| Metric |Value|
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|---------------------------------|----:|
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|Avg. |69.66|
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|AI2 Reasoning Challenge (25-Shot)|66.55|
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|HellaSwag (10-Shot) |83.45|
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|MMLU (5-Shot) |62.77|
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|TruthfulQA (0-shot) |65.16|
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|Winogrande (5-shot) |77.51|
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|GSM8k (5-shot) |62.55|
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