--- license: apache-2.0 library_name: transformers tags: - mergekit - merge - not-for-all-audiences base_model: - bamec66557/VICIOUS_MESH-12B-ALPHA - Infermatic/MN-12B-Inferor-v0.1 - Khetterman/DarkAtom-12B-v3 model-index: - name: VICIOUS_MESH-12B-BETA 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: 67.21 name: strict accuracy source: url: >- https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=bamec66557/VICIOUS_MESH-12B-BETA 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: 31.36 name: normalized accuracy source: url: >- https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=bamec66557/VICIOUS_MESH-12B-BETA 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: 12.08 name: exact match source: url: >- https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=bamec66557/VICIOUS_MESH-12B-BETA 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: 8.84 name: acc_norm source: url: >- https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=bamec66557/VICIOUS_MESH-12B-BETA 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: 14.34 name: acc_norm source: url: >- https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=bamec66557/VICIOUS_MESH-12B-BETA 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: 29.76 name: accuracy source: url: >- https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=bamec66557/VICIOUS_MESH-12B-BETA name: Open LLM Leaderboard datasets: - open-llm-leaderboard/bamec66557__VICIOUS_MESH-12B-BETA-details - open-llm-leaderboard/bamec66557__VICIOUS_MESH-12B-ALPHA-details language: - en - ja - ru - zh - ko - es --- # [GGUF] * [ Q4_K_M.gguf ](https://huggingface.co/bamec66557/VICIOUS_MESH-12B-BETA-Q4_K_M-GGUF) # 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 [TIES](https://arxiv.org/abs/2306.01708) merge method using [Khetterman/DarkAtom-12B-v3](https://huggingface.co/Khetterman/DarkAtom-12B-v3) as a base. ### Models Merged The following models were included in the merge: * [bamec66557/VICIOUS_MESH-12B-ALPHA](https://huggingface.co/bamec66557/VICIOUS_MESH-12B-ALPHA) * [Infermatic/MN-12B-Inferor-v0.1](https://huggingface.co/Infermatic/MN-12B-Inferor-v0.1) ### Configuration The following YAML configuration was used to produce this model: ```yaml models: - model: Khetterman/DarkAtom-12B-v3 #no parameters necessary for base model - model: Infermatic/MN-12B-Inferor-v0.1 parameters: density: 0.5 weight: 0.5 - model: bamec66557/VICIOUS_MESH-12B-ALPHA parameters: density: 0.5 weight: 0.5 merge_method: ties base_model: Khetterman/DarkAtom-12B-v3 parameters: normalize: false 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/bamec66557__VICIOUS_MESH-12B-BETA-details) | Metric |Value| |-------------------|----:| |Avg. |27.26| |IFEval (0-Shot) |67.21| |BBH (3-Shot) |31.36| |MATH Lvl 5 (4-Shot)|12.08| |GPQA (0-shot) | 8.84| |MuSR (0-shot) |14.34| |MMLU-PRO (5-shot) |29.76|