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name: UltimateMerge-14B-v1-slerp
merge_method: slerp
base_model: CultriX/Enhanced-TIES-Base-v1
tokenizer_source: base
dtype: float32
out_dtype: bfloat16
parameters:
normalize: true
rescale: false
int8_mask: true
parameters:
t:
- value: 0.3 # Small value for refined tuning.
slices:
- sources:
- model: CultriX/Enhanced-TIES-Base-v1 #Base model.
layer_range: [ 0, 8 ]
- model: arcee-ai/Virtuoso-Small-v2 #The arcee model focuses on IFEval so it is the best as the output layer
layer_range: [ 0, 8 ]
- sources:
- model: CultriX/Enhanced-TIES-Base-v1
layer_range: [ 8, 16 ]
- model: sometimesanotion/Lamarck-14B-v0.7-rc4 #Strong average score.
layer_range: [ 8, 16 ]
- sources:
- model: CultriX/Enhanced-TIES-Base-v1
layer_range: [ 16, 24 ]
- model: CultriX/Qwen2.5-14B-Hyperionv3 #Improve Reasoning benchmarks.
layer_range: [ 16, 24 ]
- sources:
- model: CultriX/Enhanced-TIES-Base-v1
layer_range: [ 24, 32 ]
- model: CultriX/Qwen2.5-14B-Hyperionv5 # General Benchmarks.
layer_range: [ 24, 32 ]
- sources:
- model: CultriX/Enhanced-TIES-Base-v1
layer_range: [ 32, 40 ]
- model: sthenno-com/miscii-14b-1225 #IFEval and BBH
layer_range: [ 32, 40 ]
- sources:
- model: CultriX/Enhanced-TIES-Base-v1
layer_range: [ 40, 48 ]
- model: arcee-ai/Virtuoso-Small-v2 #Output layer
layer_range: [ 40, 48 ] |