README.md

---
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

<a href="https://ibb.co/8XPkwP8"><img src="https://i.ibb.co/kMqZTqc/Joah.png" alt="Joah" border="0"></a><br />

오늘 부터 서로에게 빛이 되어 줄 여러분의 Merge Model

"좋아(Joah)" by AsianSoul

Soon Multi Language Model Merge based on this. First German Start (Korean / English / German) 🌍

Where to use Joah : Medical, Korean, English, Translation, Code, Science... 🎥

## 🎡 Merge Details


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?

Don't worry even if you don't get the results you want. 

I'll find the answer for you.

Soon real PoSE to extend Llama's context length to 64k with using my merge method : [reborn](https://medium.com/@puffanddmx82/reborn-elevating-model-adaptation-with-merging-for-superior-nlp-performance-f604e8e307b2)

I have found that most of merge's model outside so far do not actually have 64k in their configs. I will improve it in the next merge with my reborn. If that doesn't work, I guess I'll have to find another way, right?

256k is not possible. My computer is running out of memory. 

If you support me, i will try it on a computer with maximum specifications, also, i would like to conduct great tests by building a network with high-capacity traffic and high-speed 10G speeds for you.


### 🧶 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)

### 🛹 Ollama

Modelfile_Q5_K_M 
```
FROM joah-llama-3-koen-8b-coder-v1-Q5_K_M.gguf
TEMPLATE """
{{- if .System }}
system
<s>{{ .System }}</s>
{{- end }}
user
<s>Human:
{{ .Prompt }}</s>
assistant
<s>Assistant:
"""

SYSTEM """
친절한 챗봇으로서 상대방의 요청에 최대한 자세하고 친절하게 답하자. 모든 대답은 한국어(Korean)으로 대답해줘.
"""

PARAMETER temperature 0.7
PARAMETER num_predict 3000
PARAMETER num_ctx 4096
PARAMETER stop "<s>"
PARAMETER stop "</s>"
```

```
ollama create joah -f ./Modelfile_Q5_K_M 
```

Modelfile_Q5_K_M default, i hope you to test many upload file for my repo to change that and create ollama


### 🍎 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


```