EdgeReason is a compact verifier-backed dataset for improving small and
edge-deployable language models on tool use, structured JSON outputs,
state/table/unit/date reasoning, compact Mathlib-derived SFT, and routing
between direct answer, tool use, retrieval, clarification, and escalation.
The dataset is designed for teams training small models with SFT, DPO, RLVR,
GRPO, rejection sampling, and internal evaluation loops. It is not tied to any
model vendor or… See the full description on the dataset page:
https://huggingface.co/datasets/ulamai/EdgeReason.
