--- license: apache-2.0 library_name: transformers tags: - mergekit - merge base_model: - huihui-ai/Qwen2.5-14B-Instruct-abliterated-v2 - rombodawg/Rombos-LLM-V2.6-Qwen-14b - nbeerbower/Qwen2.5-Gutenberg-Doppel-14B model-index: - name: Robo-Gutenberg_V1.0 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: 60.08 name: strict accuracy source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Triangle104/Robo-Gutenberg_V1.0 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: 50.29 name: normalized accuracy source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Triangle104/Robo-Gutenberg_V1.0 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: 21.3 name: exact match source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Triangle104/Robo-Gutenberg_V1.0 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: 18.12 name: acc_norm source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Triangle104/Robo-Gutenberg_V1.0 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: 19.2 name: acc_norm source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Triangle104/Robo-Gutenberg_V1.0 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: 48.79 name: accuracy source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Triangle104/Robo-Gutenberg_V1.0 name: Open LLM Leaderboard --- # merge This is a merge of pre-trained language models created using [mergekit](https://github.com/cg123/mergekit). --- Model details: - ![image/webp](https://cdn-uploads.huggingface.co/production/uploads/66c1cc08453a7ef6c5fe657a/fdMmP6oLy11PYZCBp3t2S.webp) *He'll be back... or something.* Quants can be found here: - https://huggingface.co/mradermacher/Robo-Gutenberg_V1.0-GGUF https://huggingface.co/mradermacher/Robo-Gutenberg_V1.0-i1-GGUF --- ## Merge Method This model was merged using the [TIES](https://arxiv.org/abs/2306.01708) merge method using [rombodawg/Rombos-LLM-V2.6-Qwen-14b](https://huggingface.co/rombodawg/Rombos-LLM-V2.6-Qwen-14b) as a base. ### Models Merged The following models were included in the merge: * [huihui-ai/Qwen2.5-14B-Instruct-abliterated-v2](https://huggingface.co/huihui-ai/Qwen2.5-14B-Instruct-abliterated-v2) * [nbeerbower/Qwen2.5-Gutenberg-Doppel-14B](https://huggingface.co/nbeerbower/Qwen2.5-Gutenberg-Doppel-14B) ### Configuration The following YAML configuration was used to produce this model: ```yaml models: - model: rombodawg/Rombos-LLM-V2.6-Qwen-14b #no parameters necessary for base model - model: nbeerbower/Qwen2.5-Gutenberg-Doppel-14B parameters: density: 0.7 weight: 0.7 - model: huihui-ai/Qwen2.5-14B-Instruct-abliterated-v2 parameters: density: 0.5 weight: 0.5 merge_method: ties base_model: rombodawg/Rombos-LLM-V2.6-Qwen-14b parameters: normalize: false int8_mask: true dtype: float16 ``` # [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/Triangle104__Robo-Gutenberg_V1.0-details) | Metric |Value| |-------------------|----:| |Avg. |36.30| |IFEval (0-Shot) |60.08| |BBH (3-Shot) |50.29| |MATH Lvl 5 (4-Shot)|21.30| |GPQA (0-shot) |18.12| |MuSR (0-shot) |19.20| |MMLU-PRO (5-shot) |48.79|