--- language: - en license: apache-2.0 library_name: transformers tags: - mergekit - merge base_model: - eren23/ogno-monarch-jaskier-merge-7b-OH-PREF-DPO - Nondzu/Mistral-7B-Instruct-v0.2-code-ft - xingyaoww/CodeActAgent-Mistral-7b-v0.1 - beowolx/MistralHermes-CodePro-7B-v1 model-index: - name: Gonzo-Code-7B results: - task: type: text-generation name: Text Generation dataset: name: AI2 Reasoning Challenge (25-Shot) type: ai2_arc config: ARC-Challenge split: test args: num_few_shot: 25 metrics: - type: acc_norm value: 61.26 name: normalized accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Badgids/Gonzo-Code-7B name: Open LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: HellaSwag (10-Shot) type: hellaswag split: validation args: num_few_shot: 10 metrics: - type: acc_norm value: 83.67 name: normalized accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Badgids/Gonzo-Code-7B name: Open LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: MMLU (5-Shot) type: cais/mmlu config: all split: test args: num_few_shot: 5 metrics: - type: acc value: 62.77 name: accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Badgids/Gonzo-Code-7B name: Open LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: TruthfulQA (0-shot) type: truthful_qa config: multiple_choice split: validation args: num_few_shot: 0 metrics: - type: mc2 value: 56.7 source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Badgids/Gonzo-Code-7B name: Open LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: Winogrande (5-shot) type: winogrande config: winogrande_xl split: validation args: num_few_shot: 5 metrics: - type: acc value: 77.27 name: accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Badgids/Gonzo-Code-7B name: Open LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: GSM8k (5-shot) type: gsm8k config: main split: test args: num_few_shot: 5 metrics: - type: acc value: 51.4 name: accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Badgids/Gonzo-Code-7B name: Open LLM Leaderboard --- # Gonzo-Code-7B 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 [DARE](https://arxiv.org/abs/2311.03099) [TIES](https://arxiv.org/abs/2306.01708) merge method using [eren23/ogno-monarch-jaskier-merge-7b-OH-PREF-DPO](https://huggingface.co/eren23/ogno-monarch-jaskier-merge-7b-OH-PREF-DPO) as a base. ### Models Merged The following models were included in the merge: * [Nondzu/Mistral-7B-Instruct-v0.2-code-ft](https://huggingface.co/Nondzu/Mistral-7B-Instruct-v0.2-code-ft) * [xingyaoww/CodeActAgent-Mistral-7b-v0.1](https://huggingface.co/xingyaoww/CodeActAgent-Mistral-7b-v0.1) * [beowolx/MistralHermes-CodePro-7B-v1](https://huggingface.co/beowolx/MistralHermes-CodePro-7B-v1) ### Configuration The following YAML configuration was used to produce this model: ```yaml models: - model: eren23/ogno-monarch-jaskier-merge-7b-OH-PREF-DPO # No parameters necessary for base model - model: xingyaoww/CodeActAgent-Mistral-7b-v0.1 parameters: density: 0.53 weight: 0.4 - model: Nondzu/Mistral-7B-Instruct-v0.2-code-ft parameters: density: 0.53 weight: 0.3 - model: beowolx/MistralHermes-CodePro-7B-v1 parameters: density: 0.53 weight: 0.3 merge_method: dare_ties base_model: eren23/ogno-monarch-jaskier-merge-7b-OH-PREF-DPO parameters: int8_mask: true dtype: bfloat16 ``` # [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard) Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_Badgids__Gonzo-Code-7B) | Metric |Value| |---------------------------------|----:| |Avg. |65.51| |AI2 Reasoning Challenge (25-Shot)|61.26| |HellaSwag (10-Shot) |83.67| |MMLU (5-Shot) |62.77| |TruthfulQA (0-shot) |56.70| |Winogrande (5-shot) |77.27| |GSM8k (5-shot) |51.40|