--- library_name: transformers tags: - mergekit - merge base_model: - Locutusque/Llama-3-NeuralHercules-5.0-8B - NousResearch/Meta-Llama-3-8B - NousResearch/Hermes-2-Theta-Llama-3-8B - Locutusque/llama-3-neural-chat-v2.2-8b model-index: - name: Llama-3-Yggdrasil-2.0-8B results: - task: type: text-generation name: Text Generation dataset: name: IFEval (0-Shot) type: HuggingFaceH4/ifeval args: num_few_shot: 0 metrics: - type: inst_level_strict_acc and prompt_level_strict_acc value: 53.71 name: strict accuracy source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Locutusque/Llama-3-Yggdrasil-2.0-8B name: Open LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: BBH (3-Shot) type: BBH args: num_few_shot: 3 metrics: - type: acc_norm value: 26.92 name: normalized accuracy source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Locutusque/Llama-3-Yggdrasil-2.0-8B name: Open LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: MATH Lvl 5 (4-Shot) type: hendrycks/competition_math args: num_few_shot: 4 metrics: - type: exact_match value: 6.87 name: exact match source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Locutusque/Llama-3-Yggdrasil-2.0-8B name: Open LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: GPQA (0-shot) type: Idavidrein/gpqa args: num_few_shot: 0 metrics: - type: acc_norm value: 1.68 name: acc_norm source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Locutusque/Llama-3-Yggdrasil-2.0-8B name: Open LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: MuSR (0-shot) type: TAUR-Lab/MuSR args: num_few_shot: 0 metrics: - type: acc_norm value: 8.07 name: acc_norm source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Locutusque/Llama-3-Yggdrasil-2.0-8B name: Open LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: MMLU-PRO (5-shot) type: TIGER-Lab/MMLU-Pro config: main split: test args: num_few_shot: 5 metrics: - type: acc value: 24.07 name: accuracy source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Locutusque/Llama-3-Yggdrasil-2.0-8B name: Open LLM Leaderboard --- # merge This is a merge of pre-trained language models created using [mergekit](https://github.com/cg123/mergekit). ## 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: * [Locutusque/Llama-3-NeuralHercules-5.0-8B](https://huggingface.co/Locutusque/Llama-3-NeuralHercules-5.0-8B) * [NousResearch/Hermes-2-Theta-Llama-3-8B](https://huggingface.co/NousResearch/Hermes-2-Theta-Llama-3-8B) * [Locutusque/llama-3-neural-chat-v2.2-8b](https://huggingface.co/Locutusque/llama-3-neural-chat-v2.2-8b) ### Configuration The following YAML configuration was used to produce this model: ```yaml models: - model: NousResearch/Meta-Llama-3-8B # No parameters necessary for base model - model: NousResearch/Hermes-2-Theta-Llama-3-8B parameters: density: 0.6 weight: 0.55 - model: Locutusque/llama-3-neural-chat-v2.2-8b parameters: density: 0.55 weight: 0.4 - model: Locutusque/Llama-3-NeuralHercules-5.0-8B parameters: density: 0.65 weight: 0.6 merge_method: dare_ties base_model: NousResearch/Meta-Llama-3-8B parameters: int8_mask: true dtype: bfloat16 ``` # [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard) Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_Locutusque__Llama-3-Yggdrasil-2.0-8B) | Metric |Value| |-------------------|----:| |Avg. |20.22| |IFEval (0-Shot) |53.71| |BBH (3-Shot) |26.92| |MATH Lvl 5 (4-Shot)| 6.87| |GPQA (0-shot) | 1.68| |MuSR (0-shot) | 8.07| |MMLU-PRO (5-shot) |24.07|