Skip to content

README.md

Latest commit

 

History

History
36 lines (26 loc) · 2.18 KB

README.md

File metadata and controls

36 lines (26 loc) · 2.18 KB
Raw

Guess Who — Kev-0.8B on Core ML

A self-playing Guess Who over 80 real Wikipedia people (DBpedia-14 test split: artists, athletes, politicians).

  1. Scan. Kev reads each card's abstract once and answers all 12 yes/no questions in a single fused Core ML call (state + packed questions), so the whole wall — 960 decisions — fills in a few seconds.
  2. Play. A hidden person is picked; each turn asks the unused question that splits the cards still up closest to half, and every card whose answer differs from the hidden person's flips down, until one is left.

The header shows the last and median call time, decisions per second, and the running decision count. Everything runs on the GPU through Core ML; there is no input.

Run

Sources/KevGuessWhoDemo/demo.sh [model dir]            # app + Terminal: asitop on top, live model log below
swift run -c release KevGuessWhoDemo [model dir]              # app only

The app opens idle. Play (Space) plays a set of up to 4 games and stops on the last result; Pause / Play toggles mid-game; Reset (⌘R) starts a fresh set. The launcher's asitop pane asks for the sudo password (powermetrics); the tmux session is reused across launches.

The model downloads on first run from FluidInference/kev-0.8b-coreml (pinned revision, checksummed; ~3.3 GB) into the FluidUse cache; pass a directory with the same layout to use a local conversion. The first launch also compiles the GPU programs, which takes a few minutes; later launches start in well under a minute.

Numbers (M5 Pro)

~38 ms median per card (12 answers per call); a wall of 960 decisions in 3.0–3.5 s (270–320 decisions/s wall clock, including host-side tokenization and input building). A Core ML function left idle pays a 0.3–0.8 s re-setup on its next call, so every game re-warms its functions while dealing, outside the timed scan.

Data: DBpedia-14 (Zhang et al., 2015), Wikipedia text via DBpedia, CC BY-SA 3.0, fetched from the Hugging Face dataset viewer and cached; nothing is bundled. Model: Kev-0.8B (jaredpalmer/kev, Apache-2.0). The yes/no questions are the demo's own and have no gold labels; answers are Kev's.