- fine_tuning/minimax_h3: FA4 dense control, VSA sparsity 0/0.8/0.9/0.95/0.97
overfits, effective-batch-2 via gradient accumulation over two videos
(validated: both losses decline, ~10 s/step on 4x GB200), and the 2-GPU
configs kept as negative results (sp=2 backward working set OOMs 184 GiB).
- distribution_matching/minimax_h3: data-free DMD2 (rollout_mode: simulate)
overfit and its 32-GPU scale-up (8 trays, sp=4, HSDP 8x4, global batch 64
= 8 DP groups x accum 8).
- examples/train/slurm/dmd2_32xgb200.sbatch: login-node launch deriving
world size/rendezvous from the allocation, per-node /dev/shm weight cache,
per-node log dirs, CLUSTER-marked partition/account/container hooks.
- README.md in both config dirs: launch, topology/batch semantics, measured
step times, memory findings, shard cache, preprocessing.
- pyproject: explicit setuptools include list.
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
