China Telecom open-sources Xing4.0-29B-Intent for turning commands into structured parameters
AIChina Telecom's XingChen AGI lab open-sourced Xing4.0-29B-Intent, a 29B model that classifies user intents and extracts their parameters in one pass, returning unified JSON. The team reports end-to-end inference latency under 150 milliseconds and a zero-shot cold-start Micro-F1 of 70.27, which it says beats GPT-4.1. The code is on GitHub under Apache 2.0, and the model and its 2.753 million-sample dataset are on Hugging Face and ModelScope.
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Original title: China Telecom Open-Sources Xing4.0-29B-Intent to Turn Commands Into Structured Parameters