Merge Models
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Models I merged using mergekit library
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4 items
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Updated
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4
Merged Model
This is a merge of pre-trained language models created using mergekit.
This model is currently ranked #3 on the Open LLM Leaderboard among models up to 15B parameters, #4 among models up to 32B parameters and #53 among all the models!
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:
base_model: bunnycore/Phi-4-Model-Stock-v4
dtype: bfloat16
merge_method: slerp
parameters:
t:
- filter: self_attn
value: [0.0, 0.5, 0.3, 0.7, 1.0]
- filter: mlp
value: [1.0, 0.5, 0.7, 0.3, 0.0]
- value: 0.5
slices:
- sources:
- layer_range: [0, 40]
model: bunnycore/Phi-4-Model-Stock-v4
- layer_range: [0, 40]
model: bunnycore/Phi-4-RR-Shoup
Open LLM Leaderboard Evaluation Results
Detailed results can be found here
| Metric | Value |
|---|---|
| Avg. | 41.30 |
| IFEval (0-Shot) | 69.00 |
| BBH (3-Shot) | 55.80 |
| MATH Lvl 5 (4-Shot) | 43.66 |
| GPQA (0-shot) | 13.53 |
| MuSR (0-shot) | 16.68 |
| MMLU-PRO (5-shot) | 49.15 |
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the model is not deployed on the HF Inference API.
Model tree for suayptalha/Luminis-phi-4
Collection including suayptalha/Luminis-phi-4
Evaluation results
- strict accuracy on IFEval (0-Shot)Open LLM Leaderboard69.000
- normalized accuracy on BBH (3-Shot)Open LLM Leaderboard55.800
- exact match on MATH Lvl 5 (4-Shot)Open LLM Leaderboard43.660
- acc_norm on GPQA (0-shot)Open LLM Leaderboard13.530
- acc_norm on MuSR (0-shot)Open LLM Leaderboard16.680
- accuracy on MMLU-PRO (5-shot)test set Open LLM Leaderboard49.150