--- 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 Joah
오늘 부터 서로에게 빛이 되어 줄 여러분의 Merge Model "좋아(Joah)" by AsianSoul ## 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? ### 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 ```