Hugging Face introduces decision models with GEV-26B-Decide

Hugging Face introduces decision models, an interface for running models that evaluate an input state against predefined questions using choice, scoring, and yes-no primitives to output probability distributions rather than generating free text. The framework aims to standardize support across libraries like Transformers and llama.cpp, allowing for efficient classification, routing, and scoring without autoregressive overhead. Open article →