--- library_name: transformers tags: - mergekit - merge - shining-valiant - shining-valiant-2 - enigma - plum - plumcode - code - valiant - valiant-labs - llama - llama-3.1 - llama-3.1-instruct - llama-3.1-instruct-8b - llama-3 - llama-3-instruct - llama-3-instruct-8b - 8b - code - code-instruct - python - science - physics - biology - chemistry - compsci - computer-science - engineering - technical - conversational - chat - instruct base_model: - meta-llama/Llama-3.1-8B-Instruct - ValiantLabs/Llama3.1-8B-Enigma - ValiantLabs/Llama3.1-8B-ShiningValiant2 model-index: - name: Llama3.1-8B-PlumCode results: - task: type: text-generation name: Text Generation dataset: name: Winogrande (5-Shot) type: Winogrande args: num_few_shot: 5 metrics: - type: acc value: 73.16 name: acc - 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: 20.45 name: strict accuracy source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=sequelbox/Llama3.1-8B-PlumCode 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: 8.5 name: normalized accuracy source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=sequelbox/Llama3.1-8B-PlumCode 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: 2.42 name: exact match source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=sequelbox/Llama3.1-8B-PlumCode 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: 3.47 name: acc_norm source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=sequelbox/Llama3.1-8B-PlumCode 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: 8.97 name: acc_norm source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=sequelbox/Llama3.1-8B-PlumCode 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: 14.84 name: accuracy source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=sequelbox/Llama3.1-8B-PlumCode name: Open LLM Leaderboard --- # PlumCode 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 della merge method using [meta-llama/Llama-3.1-8B-Instruct](https://huggingface.co/meta-llama/Llama-3.1-8B-Instruct) as a base. ### Models Merged The following models were included in the merge: * [ValiantLabs/Llama3.1-8B-ShiningValiant2](https://huggingface.co/ValiantLabs/Llama3.1-8B-ShiningValiant2) * [ValiantLabs/Llama3.1-8B-Enigma](https://huggingface.co/ValiantLabs/Llama3.1-8B-Enigma) ### Configuration The following YAML configuration was used to produce this model: ```yaml merge_method: della dtype: bfloat16 parameters: normalize: true models: - model: ValiantLabs/Llama3.1-8B-ShiningValiant2 parameters: density: 0.5 weight: 0.3 - model: ValiantLabs/Llama3.1-8B-Enigma parameters: density: 0.5 weight: 0.25 base_model: meta-llama/Llama-3.1-8B-Instruct ``` # [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_sequelbox__Llama3.1-8B-PlumCode) | Metric |Value| |-------------------|----:| |Avg. | 9.77| |IFEval (0-Shot) |20.45| |BBH (3-Shot) | 8.50| |MATH Lvl 5 (4-Shot)| 2.42| |GPQA (0-shot) | 3.47| |MuSR (0-shot) | 8.97| |MMLU-PRO (5-shot) |14.84|