--- license: llama3.1 library_name: transformers tags: - mergekit - merge base_model: - mlabonne/Meta-Llama-3.1-8B-Instruct-abliterated - meta-llama/Meta-Llama-3.1-8B - meta-llama/Meta-Llama-3.1-8B-Instruct model-index: - name: Meta-Llama-3.1-8B-Instruct-HalfAbliterated-TIES 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: 45.51 name: strict accuracy source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=gaverfraxz/Meta-Llama-3.1-8B-Instruct-HalfAbliterated-TIES 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: 28.91 name: normalized accuracy source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=gaverfraxz/Meta-Llama-3.1-8B-Instruct-HalfAbliterated-TIES 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: 11.63 name: exact match source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=gaverfraxz/Meta-Llama-3.1-8B-Instruct-HalfAbliterated-TIES 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: 2.24 name: acc_norm source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=gaverfraxz/Meta-Llama-3.1-8B-Instruct-HalfAbliterated-TIES 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: 6.59 name: acc_norm source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=gaverfraxz/Meta-Llama-3.1-8B-Instruct-HalfAbliterated-TIES 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: 29.76 name: accuracy source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=gaverfraxz/Meta-Llama-3.1-8B-Instruct-HalfAbliterated-TIES name: Open LLM Leaderboard --- # Meta-Llama-3.1-8B-Instruct-HalfAbliterated-TIES 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 [TIES](https://arxiv.org/abs/2306.01708) merge method using [meta-llama/Meta-Llama-3.1-8B](https://huggingface.co/meta-llama/Meta-Llama-3.1-8B) as a base. ### Models Merged The following models were included in the merge: * [mlabonne/Meta-Llama-3.1-8B-Instruct-abliterated](https://huggingface.co/mlabonne/Meta-Llama-3.1-8B-Instruct-abliterated) * [meta-llama/Meta-Llama-3.1-8B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3.1-8B-Instruct) ### Configuration The following YAML configuration was used to produce this model: ```yaml base_model: meta-llama/Meta-Llama-3.1-8B chat_template: auto dtype: float16 merge_method: ties models: - model: mlabonne/Meta-Llama-3.1-8B-Instruct-abliterated parameters: density: 0.5 weight: 0.5 - model: meta-llama/Meta-Llama-3.1-8B-Instruct parameters: density: 0.5 weight: 0.5 parameters: int8_mask: true normalize: false ``` # [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_gaverfraxz__Meta-Llama-3.1-8B-Instruct-HalfAbliterated-TIES) | Metric |Value| |-------------------|----:| |Avg. |20.77| |IFEval (0-Shot) |45.51| |BBH (3-Shot) |28.91| |MATH Lvl 5 (4-Shot)|11.63| |GPQA (0-shot) | 2.24| |MuSR (0-shot) | 6.59| |MMLU-PRO (5-shot) |29.76|