ModelScope(@ModelScope2022):Phocinae-Largha-150M-v1 is now released, a 144.3M bilingual model that handles routine agent decisions locally with zero generation tokens.📜 Apache 2.0. 🤖 https://t.co/GCsVALogox 🎯 Handles yes/no, pick-one, and 2–10 scoring questions with calibrated confidence in a single forward pass. 🏆 Scores 0.906 on the fitted English typed-decisions evaluation and 0.848 on the in-mix Chinese evaluation. ⚡ Delivers 21 ms GPU latency in the reported RTX 5090 setup; its FP16 weights occupy just 288.6 MB and CPU inference is supported. 💰 At a confidence threshold of 0.6, its escalation router reduces LLM calls by 55% while retaining 0.9936 accuracy on the high-confidence subset.

ModelScope@ModelScope2022

2026.10.10 03:29

Phocinae-Largha-150M-v1 is now released, a 144.3M bilingual model that handles routine agent decisions locally with zero generation tokens.📜 Apache 2.0. 🤖 🎯 Handles yes/no, pick-one, and 2–10 scoring questions with calibrated confidence in a single forward pass. 🏆 Scores 0.906 on the fitted English typed-decisions evaluation and 0.848 on the in-mix Chinese evaluation. ⚡ Delivers 21 ms GPU latency in the reported RTX 5090 setup; its FP16 weights occupy just 288.6 MB and CPU inference is supported. 💰 At a confidence threshold of 0.6, its escalation router reduces LLM calls by 55% while retaining 0.9936 accuracy on the high-confidence subset.