Multi-turn chess SFT checkpoints trained after the YaRN positional-encoding fix in sfttrainer.py (2026-09). Before the fix, the blocksize / ropescaling change was applied after frompretrained(), so runs with a 3072-token context trained with plain RoPE extrapolation while their saved config claimed YaRN. These runs load the config first and build the model from it, so training and inference both use YaRN (factor 3, 1024 → 3072). Thanks to Jens Tuyls for spotting the bug. Folders mirror the local save tree. Each model lives at /final/, where modelid = C{compute}{size}alpha{α}beta{β}. Alongside final/ are combinedeval.json (when evaluated) and configsnapshot/ (training config). Optimizer…
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