merge
This is a merge of pre-trained language models created using mergekit.
Merge Details
Merge Method
This model was merged using the Model Stock merge method using ZeroXClem/Qwen-2.5-Aether-SlerpFusion-7B + bunnycore/Qwen-2.5-7b-rp-lora as a base.
Models Merged
The following models were included in the merge:
- bespokelabs/Bespoke-Stratos-7B
- Sakalti/light-7b-beta
- ZeroXClem/Qwen-2.5-Aether-SlerpFusion-7B
- deepseek-ai/DeepSeek-R1-Distill-Qwen-7B
- fblgit/cybertron-v4-qw7B-MGS + bunnycore/Qwen-2.5-7b-rp-lora
Configuration
The following YAML configuration was used to produce this model:
merge_method: model_stock
base_model: ZeroXClem/Qwen-2.5-Aether-SlerpFusion-7B+bunnycore/Qwen-2.5-7b-rp-lora
tokenizer_source: base
dtype: float32
out_dtype: bfloat16
parameters:
int8_mask: true
normalize: true
rescale: false
models:
- model: deepseek-ai/DeepSeek-R1-Distill-Qwen-7B
- model: ZeroXClem/Qwen-2.5-Aether-SlerpFusion-7B
- model: ZeroXClem/Qwen-2.5-Aether-SlerpFusion-7B+bunnycore/Qwen-2.5-7b-rp-lora
- model: Sakalti/light-7b-beta
- model: fblgit/cybertron-v4-qw7B-MGS+bunnycore/Qwen-2.5-7b-rp-lora
- model: bespokelabs/Bespoke-Stratos-7B
Open LLM Leaderboard Evaluation Results
Detailed results can be found here
Metric | Value |
---|---|
Avg. | 27.38 |
IFEval (0-Shot) | 56.95 |
BBH (3-Shot) | 34.08 |
MATH Lvl 5 (4-Shot) | 25.53 |
GPQA (0-shot) | 3.69 |
MuSR (0-shot) | 9.96 |
MMLU-PRO (5-shot) | 34.06 |
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Evaluation results
- strict accuracy on IFEval (0-Shot)Open LLM Leaderboard56.950
- normalized accuracy on BBH (3-Shot)Open LLM Leaderboard34.080
- exact match on MATH Lvl 5 (4-Shot)Open LLM Leaderboard25.530
- acc_norm on GPQA (0-shot)Open LLM Leaderboard3.690
- acc_norm on MuSR (0-shot)Open LLM Leaderboard9.960
- accuracy on MMLU-PRO (5-shot)test set Open LLM Leaderboard34.060