merge
This is a merge of pre-trained language models created using mergekit.
Merge Details
Merge Method
This model was merged using the linear merge method using huihui-ai/Llama-3.2-3B-Instruct-abliterated as a base.
Models Merged
The following models were included in the merge:
- passing2961/Thanos-3B
- prithivMLmods/Llama-Sentient-3.2-3B-Instruct
- bunnycore/Llama-3.2-3B-RP-DeepThink
- bunnycore/Llama-3.2-3B-All-Mix
- prithivMLmods/Codepy-Deepthink-3B
- HuggingFaceTB/finemath-ablation-infiwebmath
Configuration
The following YAML configuration was used to produce this model:
merge_method: linear
dtype: bfloat16
normalize: true
base_model: huihui-ai/Llama-3.2-3B-Instruct-abliterated
models:
- model: bunnycore/Llama-3.2-3B-All-Mix
parameters:
weight: 10
density: 1
- model: prithivMLmods/Codepy-Deepthink-3B
parameters:
weight: 7
density: 0.8
- model: huihui-ai/Llama-3.2-3B-Instruct-abliterated
parameters:
weight: 10
density: 1
- model: HuggingFaceTB/finemath-ablation-infiwebmath
parameters:
weight: 7
density: 0.8
- model: prithivMLmods/Llama-Sentient-3.2-3B-Instruct
parameters:
weight: 7
density: 0.8
- model: passing2961/Thanos-3B
parameters:
weight: 7
density: 0.8
- model: bunnycore/Llama-3.2-3B-RP-DeepThink
parameters:
weight: 7
density: 0.8
Open LLM Leaderboard Evaluation Results
Detailed results can be found here
Metric | Value |
---|---|
Avg. | 22.47 |
IFEval (0-Shot) | 66.79 |
BBH (3-Shot) | 23.04 |
MATH Lvl 5 (4-Shot) | 13.52 |
GPQA (0-shot) | 3.58 |
MuSR (0-shot) | 3.15 |
MMLU-PRO (5-shot) | 24.76 |
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Evaluation results
- strict accuracy on IFEval (0-Shot)Open LLM Leaderboard66.790
- normalized accuracy on BBH (3-Shot)Open LLM Leaderboard23.040
- exact match on MATH Lvl 5 (4-Shot)Open LLM Leaderboard13.520
- acc_norm on GPQA (0-shot)Open LLM Leaderboard3.580
- acc_norm on MuSR (0-shot)Open LLM Leaderboard3.150
- accuracy on MMLU-PRO (5-shot)test set Open LLM Leaderboard24.760