--- library_name: transformers tags: - mergekit - merge base_model: - nbeerbower/Mistral-Nemo-Gutenberg-Doppel-12B-v2 - Fizzarolli/MN-12b-Sunrose - anthracite-org/magnum-v4-12b - mistralai/Mistral-Nemo-Instruct-2407 model-index: - name: MN-12B-Inferor-v0.1 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: 63.47 name: strict accuracy source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Svak/MN-12B-Inferor-v0.1 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-v0.1 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: 11.78 name: exact match source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Svak/MN-12B-Inferor-v0.1 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: 10.07 name: acc_norm source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Svak/MN-12B-Inferor-v0.1 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: 15.05 name: acc_norm source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Svak/MN-12B-Inferor-v0.1 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: 29.58 name: accuracy source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Svak/MN-12B-Inferor-v0.1 name: Open LLM Leaderboard --- # inferor 0.1 Another iteration of inferor but with different base model ![image/png](https://cdn-uploads.huggingface.co/production/uploads/64be962a38953777feaabfc0/VflBXBEkNWGwfK_xVQQis.png) 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 [mistralai/Mistral-Nemo-Instruct-2407](https://huggingface.co/mistralai/Mistral-Nemo-Instruct-2407) 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) * [Fizzarolli/MN-12b-Sunrose](https://huggingface.co/Fizzarolli/MN-12b-Sunrose) * [anthracite-org/magnum-v4-12b](https://huggingface.co/anthracite-org/magnum-v4-12b) ### Configuration The following YAML configuration was used to produce this model: ```yaml base_model: mistralai/Mistral-Nemo-Instruct-2407 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: anthracite-org/magnum-v4-12b - layer_range: [0, 40] model: mistralai/Mistral-Nemo-Instruct-2407 ``` # [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-v0.1) | Metric |Value| |-------------------|----:| |Avg. |26.80| |IFEval (0-Shot) |63.47| |BBH (3-Shot) |30.85| |MATH Lvl 5 (4-Shot)|11.78| |GPQA (0-shot) |10.07| |MuSR (0-shot) |15.05| |MMLU-PRO (5-shot) |29.58|