---
base_model:
- beomi/Llama-3-KoEn-8B-Instruct-preview
- Danielbrdz/Barcenas-Llama3-8b-ORPO
- maum-ai/Llama-3-MAAL-8B-Instruct-v0.1
- rombodawg/Llama-3-8B-Instruct-Coder
- NousResearch/Meta-Llama-3-8B-Instruct
- rombodawg/Llama-3-8B-Base-Coder-v3.5-10k
- cognitivecomputations/dolphin-2.9-llama3-8b
- asiansoul/Llama-3-Open-Ko-Linear-8B
- NousResearch/Meta-Llama-3-8B
- aaditya/Llama3-OpenBioLLM-8B
library_name: transformers
tags:
- mergekit
- merge

---
# Joah-Llama-3-KoEn-8B-Coder-v1

"오늘 부터 서로에게 빛이 되어 줄 여러분의 Merge Model

좋아(Joah) by AsianSoul"

The performance of this merge model doesn't seem to be bad though.-> Just opinion

This may not be a model that satisfies you. But if we continue to overcome our shortcomings, won't we someday find the answer we want?

## Merge Details
### 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 [NousResearch/Meta-Llama-3-8B](https://huggingface.co/NousResearch/Meta-Llama-3-8B) as a base.

### Models Merged

The following models were included in the merge:
* [beomi/Llama-3-KoEn-8B-Instruct-preview](https://huggingface.co/beomi/Llama-3-KoEn-8B-Instruct-preview)
* [Danielbrdz/Barcenas-Llama3-8b-ORPO](https://huggingface.co/Danielbrdz/Barcenas-Llama3-8b-ORPO)
* [maum-ai/Llama-3-MAAL-8B-Instruct-v0.1](https://huggingface.co/maum-ai/Llama-3-MAAL-8B-Instruct-v0.1)
* [rombodawg/Llama-3-8B-Instruct-Coder](https://huggingface.co/rombodawg/Llama-3-8B-Instruct-Coder)
* [NousResearch/Meta-Llama-3-8B-Instruct](https://huggingface.co/NousResearch/Meta-Llama-3-8B-Instruct)
* [rombodawg/Llama-3-8B-Base-Coder-v3.5-10k](https://huggingface.co/rombodawg/Llama-3-8B-Base-Coder-v3.5-10k)
* [cognitivecomputations/dolphin-2.9-llama3-8b](https://huggingface.co/cognitivecomputations/dolphin-2.9-llama3-8b)
* [asiansoul/Llama-3-Open-Ko-Linear-8B](https://huggingface.co/asiansoul/Llama-3-Open-Ko-Linear-8B)
* [aaditya/Llama3-OpenBioLLM-8B](https://huggingface.co/aaditya/Llama3-OpenBioLLM-8B)

### Configuration

The following YAML configuration was used to produce this model:

```yaml
models:
  - model: NousResearch/Meta-Llama-3-8B
    # Base model providing a general foundation without specific parameters

  - model: NousResearch/Meta-Llama-3-8B-Instruct
    parameters:
      density: 0.60  
      weight: 0.25  
  
  - model: beomi/Llama-3-KoEn-8B-Instruct-preview
    parameters:
      density: 0.55  
      weight: 0.15  
  
  - model: asiansoul/Llama-3-Open-Ko-Linear-8B
    parameters:
      density: 0.55  
      weight: 0.2  

  - model: maum-ai/Llama-3-MAAL-8B-Instruct-v0.1
    parameters:
      density: 0.55  
      weight: 0.1 

  - model: rombodawg/Llama-3-8B-Instruct-Coder
    parameters:
      density: 0.55  
      weight: 0.1
      
  - model: rombodawg/Llama-3-8B-Base-Coder-v3.5-10k
    parameters:
      density: 0.55  
      weight: 0.1  

  - model: cognitivecomputations/dolphin-2.9-llama3-8b
    parameters:
      density: 0.55  
      weight: 0.05  

  - model: Danielbrdz/Barcenas-Llama3-8b-ORPO
    parameters:
      density: 0.55  
      weight: 0.05 

  - model: aaditya/Llama3-OpenBioLLM-8B
    parameters:
      density: 0.55  
      weight: 0.1 

merge_method: dare_ties
base_model: NousResearch/Meta-Llama-3-8B
parameters:
  int8_mask: true
dtype: bfloat16


```