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:
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: 7
density: 0.8
Open LLM Leaderboard Evaluation Results
Detailed results can be found here
| Metric | Value |
|---|---|
| Avg. | 23.06 |
| IFEval (0-Shot) | 71.44 |
| BBH (3-Shot) | 23.76 |
| MATH Lvl 5 (4-Shot) | 15.18 |
| GPQA (0-shot) | 2.13 |
| MuSR (0-shot) | 0.94 |
| MMLU-PRO (5-shot) | 24.91 |
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Evaluation results
- strict accuracy on IFEval (0-Shot)Open LLM Leaderboard71.440
- normalized accuracy on BBH (3-Shot)Open LLM Leaderboard23.760
- exact match on MATH Lvl 5 (4-Shot)Open LLM Leaderboard15.180
- acc_norm on GPQA (0-shot)Open LLM Leaderboard2.130
- acc_norm on MuSR (0-shot)Open LLM Leaderboard0.940
- accuracy on MMLU-PRO (5-shot)test set Open LLM Leaderboard24.910