AGP/N'Ko Thunder Train Status

Thunder Train is active again for MLX-based distributed adapter training across Mac4 and Mac5. It applies directly to the Gemma/AGP corrective language layer, including LoRA adapter training and tensor/data parallel experiments. It does not automatically apply to the current Paper 4 N'Ko ASR checkpoint because that checkpoint is a PyTorch Whisper-large-v3 trajectory model. To use Thunder Train for that layer, the ASR model would need an MLX training/inference port or a separate MLX-compatible acoustic adapter design. - Mac4: `[ip]`, MLX `0.31.1`, MLX-LM `0.31.2` - Mac5: `[ip]`, MLX `0.31.1`, MLX-LM `0.31.2` - Thunderbolt bridge: - Mac4 -> Mac5: about `0.52ms` - Mac5 -> Mac4: about `0.56ms` - MLX distributed ring smoke: - rank 0 reported `size=2` - rank 1 reported `size=2` - all-sum check passed on both ranks - Builder: `scripts/build_agp_nko_correction_chatml.py` - Manifest: `data/agp-nko-corrections/manifest.json` - Train rows: `16` - Validation rows: `4` - Source reports: - `policy_smoke_http_fewshot_rust_gate` - `synthetic_http_fewshot_rust_gate` - `eval_results_base_lowcer_http_rust_gate` - world size: `2` - strategy: `data` - LoRA: rank `8`, last `4` layers - trainable params: `15,877,411` - validation loss: - step 2: `3.7663` - step 4/final: `3.7460` - adapter artifact: - Mac4 rank-0 path: `[home-path]` - mirrored local path: `[home-path]` - size: about `61M`