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 ]