2026-09-28 · America/Los_Angeles · 社区动态 · #5

Trained locally: ultra-fast 0.8B/2B System 1 decision models that match Jev on benchmarks and Doom, ~30 ms per decision (open weights)

TL;DR: The Jeff models are a set of Qwen3.5 and Gemma fine-tunes for zero-shot classification: small, efficient, open-weight models with respectable out-of-the-box performance that can be slotted right into code or fine-tuned/LoRA-trained as needed. Give them a situation and a list of options; they return a calibrated probability for each, in one forward pass, no text generation. The 2B scores 83.1% on a five-benchmark panel (Jev's published figure: 83.0%); the 0.8B decides in ~28 ms on an M4 Max (see caveats below). Maybe equally exciting for open model enthusiasts like myself, everything…

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