The training UI's 'Standard' option sends the string "true". The worker
converted "false"/"none"/"" to False but passed "true" through as a string.
unsloth's _configure_gradient_checkpointing only unpatches the smart
offloader on the (True, False) boolean branch; the string "true" matches
neither that nor "unsloth", so it returns without unpatching and the
offloader stays active. On memory-constrained / unified-memory GPUs that
offload then OOM-crashes even though the user asked for standard
checkpointing (reported on gfx1201 R9700, applies to Strix Halo too).
Normalize "true"/"1"/"yes" -> True so unsloth gets a real bool and
unpatches, matching the existing normalization in trainer.py. "unsloth"
and "mlx" stay strings; booleans pass through unchanged.
3b16e317b8