--- library_name: transformers tags: - mergekit - merge base_model: - nbeerbower/Mistral-Nemo-Gutenberg-Doppel-12B-v2 - nothingiisreal/MN-12B-Starcannon-v3 - anthracite-org/magnum-v4-12b - Fizzarolli/MN-12b-Sunrose model-index: - name: MN-12B-Inferor-v0.0 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: 57.08 name: strict accuracy source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Svak/MN-12B-Inferor-v0.0 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: 30.85 name: normalized accuracy source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Svak/MN-12B-Inferor-v0.0 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: 10.05 name: exact match source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Svak/MN-12B-Inferor-v0.0 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: 7.83 name: acc_norm source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Svak/MN-12B-Inferor-v0.0 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: 18.09 name: acc_norm source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Svak/MN-12B-Inferor-v0.0 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: 28.43 name: accuracy source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Svak/MN-12B-Inferor-v0.0 name: Open LLM Leaderboard --- ![image/png](https://cdn-uploads.huggingface.co/production/uploads/64be962a38953777feaabfc0/DncyZQ6V2NAEfFeEerxcw.png) # Inferor My first merge yay! #### This was made thanks to [infermatic.ai](https://infermatic.ai/) 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 [Model Stock](https://arxiv.org/abs/2403.19522) merge method using [anthracite-org/magnum-v4-12b](https://huggingface.co/anthracite-org/magnum-v4-12b) as a base. ### Models Merged The following models were included in the merge: * [nbeerbower/Mistral-Nemo-Gutenberg-Doppel-12B-v2](https://huggingface.co/nbeerbower/Mistral-Nemo-Gutenberg-Doppel-12B-v2) * [nothingiisreal/MN-12B-Starcannon-v3](https://huggingface.co/nothingiisreal/MN-12B-Starcannon-v3) * [Fizzarolli/MN-12b-Sunrose](https://huggingface.co/Fizzarolli/MN-12b-Sunrose) ### Configuration The following YAML configuration was used to produce this model: ```yaml base_model: anthracite-org/magnum-v4-12b dtype: bfloat16 merge_method: model_stock slices: - sources: - layer_range: [0, 40] model: Fizzarolli/MN-12b-Sunrose - layer_range: [0, 40] model: nbeerbower/Mistral-Nemo-Gutenberg-Doppel-12B-v2 - layer_range: [0, 40] model: nothingiisreal/MN-12B-Starcannon-v3 - layer_range: [0, 40] model: anthracite-org/magnum-v4-12b ``` # [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_Svak__MN-12B-Inferor-v0.0) | Metric |Value| |-------------------|----:| |Avg. |25.39| |IFEval (0-Shot) |57.08| |BBH (3-Shot) |30.85| |MATH Lvl 5 (4-Shot)|10.05| |GPQA (0-shot) | 7.83| |MuSR (0-shot) |18.09| |MMLU-PRO (5-shot) |28.43|