--- library_name: transformers tags: - mergekit - merge base_model: - cognitivecomputations/dolphin-2.2.1-mistral-7b - teknium/OpenHermes-2.5-Mistral-7B model-index: - name: RuDolph-Hermes-7B 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: 36.04 name: strict accuracy source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=theprint/RuDolph-Hermes-7B 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: 30.71 name: normalized accuracy source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=theprint/RuDolph-Hermes-7B 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: 5.06 name: exact match source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=theprint/RuDolph-Hermes-7B 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: 8.28 name: acc_norm source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=theprint/RuDolph-Hermes-7B 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: 11.03 name: acc_norm source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=theprint/RuDolph-Hermes-7B 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: 23.03 name: accuracy source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=theprint/RuDolph-Hermes-7B name: Open LLM Leaderboard --- # Meet Rudolph Finn Hermes This model is an homage to two of my all-time favorite versions of the Mistral 7B model, Dolphin and OpenHermes. Hence the silly name. It's a good conversational model. The image is generated from a prompt written by the model, after being told to seek inspiration from its name. This is a merge of pre-trained language models created using [mergekit](https://github.com/cg123/mergekit). ## GGUF Versions If you're looking for a GGUF-version, here's where to find some: - [mradermacher/RuDolph-Hermes-7B-GGUF](https://huggingface.co/mradermacher/RuDolph-Hermes-7B-GGUF) - [mradermacher/RuDolph-Hermes-7B-i1-GGUF](https://huggingface.co/mradermacher/RuDolph-Hermes-7B-i1-GGUF) (imatrix quants) ## Merge Details ### Merge Method This model was merged using the SLERP merge method with a Sigmoid-inspired curve. ### Models Merged The following models were included in the merge: * [cognitivecomputations/dolphin-2.2.1-mistral-7b](https://huggingface.co/cognitivecomputations/dolphin-2.2.1-mistral-7b) * [teknium/OpenHermes-2.5-Mistral-7B](https://huggingface.co/teknium/OpenHermes-2.5-Mistral-7B) ### Configuration The following YAML configuration was used to produce this model: ```yaml models: - model: teknium/OpenHermes-2.5-Mistral-7B - model: cognitivecomputations/dolphin-2.2.1-mistral-7b merge_method: slerp base_model: teknium/OpenHermes-2.5-Mistral-7B dtype: bfloat16 parameters: t: [0.2, 0.3, 0.5, 0.7, 0.8] ``` # [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_theprint__RuDolph-Hermes-7B) | Metric |Value| |-------------------|----:| |Avg. |19.02| |IFEval (0-Shot) |36.04| |BBH (3-Shot) |30.71| |MATH Lvl 5 (4-Shot)| 5.06| |GPQA (0-shot) | 8.28| |MuSR (0-shot) |11.03| |MMLU-PRO (5-shot) |23.03|