File size: 1,800 Bytes
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models:
- model: VAGOsolutions/SauerkrautLM-v2-14b-DPO
parameters:
weight: 0.20 # Strong IFEval and factual reasoning baseline
density: 0.6
- model: allknowingroger/QwenSlerp6-14B
parameters:
weight: 0.20 # Balanced reasoning across multiple benchmarks
density: 0.6
- model: CultriX/SeQwence-14B-EvolMerge
parameters:
weight: 0.15 # Generalist model for BBH and MUSR
density: 0.5
- model: CultriX/Qwen2.5-14B-Wernicke
parameters:
weight: 0.15 # QA leader for GPQA and MUSR
density: 0.6 # Increase density to preserve more QA-specific parameters
- model: qingy2019/Qwen2.5-Math-14B-Instruct
parameters:
weight: 0.15 # Specialist for MATH and advanced reasoning
density: 0.6
- model: sometimesanotion/Qwen2.5-14B-Vimarckoso
parameters:
weight: 0.10 # MUSR leader for nuanced multi-step reasoning
density: 0.5
- model: CultriX/Qwen2.5-14B-SLERPv7
parameters:
weight: 0.05 # Contextual reasoning support for BBH and tiny benchmarks
density: 0.5
base_model: CultriX/SeQwence-14Bv1
merge_method: dare_ties
parameters:
normalize: true
int8_mask: true
dtype: bfloat16
adaptive_merge_parameters:
task_weights:
IFEval: 1.3 # Enhanced instruction-following and factual tasks
BBH: 1.3 # Strengthened complex reasoning capabilities
MATH_Lvl_5: 1.4 # Prioritize advanced mathematical tasks
GPQA: 1.4 # Boost graduate-level knowledge capabilities
MuSR: 1.3 # Strengthen multi-step reasoning on complex tasks
MMLU_PRO: 1.2 # Ensure broad domain understanding
smoothing_factor: 0.15 # Sharper blending for reasoning and factual tasks
gradient_clipping: 0.9 # Tighter control for precise parameter scaling
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