numpy has no bfloat16, so .numpy().tobytes() raised
'TypeError: Got unsupported ScalarType BFloat16' on real checkpoints.
Flatten then view(torch.uint8) before hashing.
Result on the heresy candidate: VERDICT IDENTICAL -- all 15 mtp.* tensors
byte-identical to the incumbent's verbatim base graft, the head already
measured at 47.7% acceptance in production. The ~56 GB bf16 acceptance gate
is redundant, so no second seat comes down.
vh
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