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### CONFIG SuperiorMerge-14B-From-2-to-10 ###
models:
- model: VAGOsolutions/SauerkrautLM-v2-14b-DPO
parameters:
weight: 0.25 # Prioritize top IFEval
density: 0.6 # Keep a large portion for strong factual baseline
- model: allknowingroger/QwenSlerp6-14B
parameters:
weight: 0.25 # High weight for MATH and balanced reasoning
density: 0.6 # Retain robust reasoning capabilities
- model: CultriX/SeQwence-14B-EvolMerge
parameters:
weight: 0.20 # Important for best BBH and near-top MUSR
density: 0.5 # Moderate density to ensure these strengths blend well
- model: CultriX/Qwen2.5-14B-Wernicke
parameters:
weight: 0.15 # Adds top GPQA performance
density: 0.5 # Sufficient to preserve QA strengths
- model: allknowingroger/QwenStock3-14B
parameters:
weight: 0.15 # For top MMLU-PRO, enhancing domain knowledge
density: 0.5 # Balanced integration of diverse subject expertise
base_model: Qwen/Qwen2.5-14B
merge_method: dare_ties
parameters:
normalize: true # Ensures parameter scaling compatibility
int8_mask: true # Memory and computational efficiency
dtype: bfloat16
tokenizer_source: Qwen/Qwen2.5-14B-Instruct
### END OF CONFIG SuperiorMerge-14B-From-2-to-10 ###
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