# CoralLM merge config (mergekit)
# Method: TIES — trims each finetune's task vector to its strongest deltas,
# elects a consensus sign per parameter, then merges. Stable and
# quality-preserving on Llama-3.2-1B (same method bunnycore's popular
# 1B/3B merges use). Swap merge_method to dare_ties to experiment.
#
# Run:
#   pip install mergekit
#   mergekit-yaml corallm_merge.yml ./corallm-merge --cuda
#
# Note: meta-llama/Llama-3.2-1B-Instruct is GATED. Before running:
#   huggingface-cli login        (and accept the license on the model page)

base_model: meta-llama/Llama-3.2-1B-Instruct   # reference anchor, not a contributor
merge_method: ties
dtype: float16
parameters:
  normalize: true        # keep merged magnitudes in check across 4 contributors
  int8_mask: true        # memory-light sign mask

models:
  # --- Reasoning (split across two sources so it doesn't dominate) ---
  - model: EpistemeAI/Reasoning-Llama-3.2-1B-Instruct-v1.2
    parameters:
      weight: 0.30
      density: 0.5
  - model: Predacon/Pico-Lamma-3.2-1B-Reasoning-Instruct
    parameters:
      weight: 0.20
      density: 0.5

  # --- Math / coding / logic ---
  - model: ai-nexuz/llama-3.2-1b-instruct-fine-tuned
    parameters:
      weight: 0.30
      density: 0.5

  # --- General / creative / roleplay (loosens Meta's sterile alignment) ---
  - model: bunnycore/Llama-3.2-1B-General-Best
    parameters:
      weight: 0.25
      density: 0.5