A 187M-param zero-shot classifier plays Doom 10x faster with a single forward pass
max_paperclips · x · 2026-09-17
Nathan Wilbanks hooked Doom to a small 187M-parameter zero-shot sequence classification model, deriving actions via a single forward pass and running 10x+ faster than comparable approaches — a replication of the viral low-latency decision model Jev.
He notes the same recipe applies to business tasks like intent detection, task prioritization, customer support routing, and scoring.
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