Clef: Open-source decision models, and new RL fine-tuning platform

In one line

We are introducing Clef and Clef-flash, open-source decision models hosted on Workers AI for high-speed classification and agentic workflows. Also launching: a new reinforcement learning platform that allows developers to fine-tune decision models using their own data.

Opening excerpt

Over the last few weeks, there has been lots of buzz around decision models such as Typesafe AI’s Jev System One model. While classifier models have been around for some time, Jev introduces a new decision model concept into the world of AI — a model that produces bounded structured outputs cheaply, quickly and consistently that can be added into a workflow when a decision is required. These models are capable enough to work over any set of inputs without constantly retraining the model to incorporate new classification categories. This contrasts with the world of Large Language Models (LLMs), which are largely non-deterministic, but are open-ended enough to reason and generate text and tool calls for agentic workloads.

Today, we’re releasing two Cloudflare-trained decision models, Clef and Clef-flash, hosted on Workers AI . Clef is currently the leader when evaluated against the Jev Decision Index , you can view full results on the live benchmark demo site . These models are smarter, faster, and fully Jev-API compatible, so you can experiment with these hosted models easily.

(Excerpted from the original; full article via the source link below.)

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