Post on X
- Views
- 140,049
- Likes
- 1,521
- Reposts
- 190
Read from X on . Counts change daily.
Use casesSupport inbox triage
Introducing Clef: our open-source decision models, and new RL fine-tuning platform
Cloudflare's launch post for Clef and Clef-flash, two decision models on Workers AI that accept the Jev request format and open weights under Apache 2.0. It covers the architecture, Cloudflare's own benchmark tables against Jev, Kev and Laya, and a new reinforcement learning service.
More like this
SetFit: efficient few-shot text classification
Fine-tunes Sentence Transformer embeddings plus a lightweight head for high-accuracy classification from a handful of labeled examples, with no prompting. The standard cheap alternative to an LLM classification call when the label set is fixed. Star count is GitHub's rounded display figure.
GLiNER2.5-Decide
Open-weights 340M-parameter decision model from Fastino Labs. It jointly decodes typed classification questions and, per Fastino's own internal benchmark, leads 9 of 17 datasets against JevK5, SemIf and Laya.
Fastino Labs (@fastinoAI)OpenGLiNER2.5-Decide on huggingface.co2.2k starsCPU latency 167 msGPU latency 38-47 ms
ModernBERT
Modernized BERT encoder used as the backbone for fast fine-tuned classifiers and rerankers. The non-generative baseline Jev's cost and latency claims are usually measured against. Star count is GitHub's rounded display figure.
pg-jev
PostgreSQL extension that lets you filter, rank and classify rows with plain-language conditions, such as WHERE jev(tickets, 'the customer is angry'). Adds jev_prob, jev_choice and jev_score functions that compose with joins, GROUP BY and ORDER BY, with no index or embeddings. Published on PGXN.
realZachiOpenpg-jev on github.com329 stars2k rows, cold ~3.5s, $0.0122k rows, cached ~50ms
shiftynick/jev-axi
Agent-ergonomic CLI for Jev with pick, rate, check, rank, triage and guard subcommands, meant for agents offloading snap judgments from the shell.
Jev Driving Lab / typesafe-playground
Three runnable experiments: support-message triage producing six independent judgments, a driving simulation where Jev picks lane and target speed against traffic and signs, and an alternative Fable implementation. Shows questions and probability distributions for each call.
