Llama
Collection
Meta-based models
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823 items
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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: deepseek-ai/DeepSeek-R1-Distill-Llama-8B
layer_range: [0, 32]
- model: huihui-ai/DeepSeek-R1-Distill-Llama-8B-abliterated
layer_range: [0, 32]
merge_method: slerp
base_model: deepseek-ai/DeepSeek-R1-Distill-Llama-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. | 19.57 |
| IFEval (0-Shot) | 35.66 |
| BBH (3-Shot) | 17.50 |
| MATH Lvl 5 (4-Shot) | 33.16 |
| GPQA (0-shot) | 5.59 |
| MuSR (0-shot) | 6.12 |
| MMLU-PRO (5-shot) | 19.37 |
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Evaluation results
- strict accuracy on IFEval (0-Shot)Open LLM Leaderboard35.660
- normalized accuracy on BBH (3-Shot)Open LLM Leaderboard17.500
- exact match on MATH Lvl 5 (4-Shot)Open LLM Leaderboard33.160
- acc_norm on GPQA (0-shot)Open LLM Leaderboard5.590
- acc_norm on MuSR (0-shot)Open LLM Leaderboard6.120
- accuracy on MMLU-PRO (5-shot)test set Open LLM Leaderboard19.370