pilot_Apc_s1

Byte-level H-Net run from beetle-hnet, trained with the legacy trainer (legacy/tier1/train.py). Split out of the bundled repo AdaptiveChunking/hnet-chunking-pilots into the Beetle per-run layout.

• step-N branches: 1 retained checkpoints (6000), each with model.safetensors and config.json (model_config, training config and the tied_weights map: restore with sd[dst] = sd[src] for every entry).
• main: the latest weights plus final.json and log.jsonl.
• The legacy trainer kept no optimiser state, so there is no training_state/ here. FLORES+ boundary probes for this run are in the dataset AdaptiveChunking/hnet-chunking-probes under pilot_Apc_s1/.