merge
This is a merge of pre-trained language models created using mergekit.
Merge Details
Merge Method
This model was merged using the SLERP merge method.
Models Merged
The following models were included in the merge:
Configuration
The following YAML configuration was used to produce this model:
slices:
- sources:
- model: meta-llama/Meta-Llama-3.1-8B
layer_range:
- 0
- 32
- model: meta-llama/Meta-Llama-3.1-8B-Instruct
layer_range:
- 0
- 32
merge_method: slerp
base_model: meta-llama/Meta-Llama-3.1-8B
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
dtype: bfloat16
Open LLM Leaderboard Evaluation Results
Detailed results can be found here
| Metric | Value |
|---|---|
| Avg. | 19.02 |
| IFEval (0-Shot) | 29.07 |
| BBH (3-Shot) | 29.93 |
| MATH Lvl 5 (4-Shot) | 10.50 |
| GPQA (0-shot) | 6.15 |
| MuSR (0-shot) | 9.37 |
| MMLU-PRO (5-shot) | 29.12 |
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Inference Providers
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the model is not deployed on the HF Inference API.
Model tree for vhab10/Llama-3.1-8B-Base-Instruct-SLERP
Evaluation results
- strict accuracy on IFEval (0-Shot)Open LLM Leaderboard29.070
- normalized accuracy on BBH (3-Shot)Open LLM Leaderboard29.930
- exact match on MATH Lvl 5 (4-Shot)Open LLM Leaderboard10.500
- acc_norm on GPQA (0-shot)Open LLM Leaderboard6.150
- acc_norm on MuSR (0-shot)Open LLM Leaderboard9.370
- accuracy on MMLU-PRO (5-shot)test set Open LLM Leaderboard29.120