mergekit_config.yml

models:
  - model: Warit2/GemOmniscien
    parameters:
      density: 0.5
      weight: 0.5
  - model: google/gemma-2b-it
    parameters:
      density: 0.5
      weight: 0.5 # weight gradient
merge_method: ties
base_model: Warit2/GemOmniscien
parameters:
  normalize: true
  int8_mask: true
dtype: bfloat16


# models:
#   - model: unsloth/gemma-7b-bnb-4bit
#     layer_range: [0, 32]
#     # no parameters necessary for base model
#   - model: mistralai/Mistral-7B-v0.1
#     layer_range: [24, 32]
# merge_method: passthrough
# # base_model: unsloth/gemma-7b-bnb-4bit
# parameters:
#   normalize: true
#   int8_mask: true
# dtype: float16
# slices:
#   - sources:
#     - model: unsloth/gemma-2b-bnb-4bit
#       layer_range: [0, 16]
#   - sources:
#     - model: NousResearch/Nous-Hermes-llama-2-7b
#       layer_range: [0, 22]
# merge_method: passthrough
# dtype: bfloat16
# models:
#   - model: unsloth/gemma-2b-bnb-4bit
#     parameters:
#       density: 0.53
#       weight: 0.45
#   - model: TinyLlama/TinyLlama-1.1B-Chat-v1.0
#     parameters:
#       weight: 0.5
# merge_method: ties
# base_model: unsloth/gemma-2b-bnb-4bit
# parameters:
#   int8_mask: true
# dtype: bfloat16