IceSakeV8RP-7b
This is a merge of pre-trained language models created using mergekit.
Merge Details
This is model only for merges!
Final model IceSakeRP-7b
Merge Method
This model was merged using the SLERP merge method.
Models Merged
The following models were included in the merge:
- IceLemonTea-IceCoffeRP-7b
- IceSakeV7RP-7b
- IceLatteRP-7b
- IceSakeV6RP-7b
Configuration
The following YAML configuration was used to produce this model:
slices:
- sources:
- model: IceLemonTea-IceCoffeRP-7b
layer_range: [0, 32]
- model: IceSakeV7RP-7b
layer_range: [0, 32]
merge_method: slerp
base_model: IceLemonTea-IceCoffeRP-7b
parameters:
t:
- filter: self_attn
value: [0, 0.5, 0.3, 0.7, 1]
- filter: mlp
value: [1, 0.5, 0.7, 0.3, 0]
- value: 0.5 # fallback for rest of tensors
dtype: float16
Open LLM Leaderboard Evaluation Results
Detailed results can be found here
Metric | Value |
---|---|
Avg. | 21.64 |
IFEval (0-Shot) | 60.86 |
BBH (3-Shot) | 28.97 |
MATH Lvl 5 (4-Shot) | 5.66 |
GPQA (0-shot) | 3.47 |
MuSR (0-shot) | 8.54 |
MMLU-PRO (5-shot) | 22.34 |
- Downloads last month
- 8
Inference Providers
NEW
This model is not currently available via any of the supported Inference Providers.
Model tree for icefog72/IceSakeV8RP-7b
Evaluation results
- strict accuracy on IFEval (0-Shot)Open LLM Leaderboard60.860
- normalized accuracy on BBH (3-Shot)Open LLM Leaderboard28.970
- exact match on MATH Lvl 5 (4-Shot)Open LLM Leaderboard5.660
- acc_norm on GPQA (0-shot)Open LLM Leaderboard3.470
- acc_norm on MuSR (0-shot)Open LLM Leaderboard8.540
- accuracy on MMLU-PRO (5-shot)test set Open LLM Leaderboard22.340