  global_ratio: 0.4893
  attn_ratio: 0.1463
  ffn_ratio: 0.8768
  embed_ratio: 0.3021
  density_a: 0.8507
  density_b: 0.9413
  block_0_ratio: 0.6750
  block_1_ratio: 0.4790
  block_2_ratio: 0.3610
  block_3_ratio: 0.4365
  block_4_ratio: 0.5255
  block_5_ratio: 0.6525
  block_6_ratio: 0.5557
  block_7_ratio: 0.2783
  block_8_ratio: 0.7302
  block_9_ratio: 0.4764
  mri_trust: 0.8571
  merge_method_weight: 0.7802

MRI Prescription Summary

Average ratio_b: 0.500
Attention ratio: 0.500
FFN ratio: 0.500
Embed ratio: 0.500
Transplant A: 0
Transplant B: 0
Blended: 1199

Health Check

failed: Repo id must be in the form 'repo_name' or 'namespace/repo_name': '/data/ray_temp/ginipick/darwin_merge_cache/merged_9cd05ed7'. Use repo_type argument if needed.

Method

Darwin V6 implements DARE-TIES merge directly via PyTorch tensor operations. Per-tensor ratios are determined by MRI diagnostic (static tensor analysis + probe-based functional importance) combined with evolutionary genome search.

Formula: final_ratio = mri_ratio * mri_trust + genome_ratio * (1 - mri_trust)

DARE-TIES algorithm: Yadav et al., 2023 (re-implemented, not library-dependent)

Built by VIDRAFT. Apache 2.0.

SeaWolf-AI/Darwin-Qwen3.5-27B-x-Qwen3.5-27B-Claude-4-08162

Darwin V6 Evolved Model

Parent Models

Evolution Result

Merge Statistics

Optimal Genome

MRI Prescription Summary

Health Check

Method

SeaWolf-AI/
Darwin-Qwen3.5-27B-x-Qwen3.5-27B-Claude-4-08162