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Developer adapts MiniCPM5-2B into a structured decision model

AIDeveloper @ActbroDev built MiniCPM5-2B-Jev on OpenBMB's MiniCPM5-2B as a System 1 decision model that returns probabilities for predefined options instead of free-form text. The project reports 78.79% on JevBench, ranking first among open-weight System 1 / Jev models at 2B parameters or fewer, and 86.41% accuracy on the 10-source decision-v7 benchmark.
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What if your model could make a structured choice instead of writing another paragraph? 🎯

Developer @ActbroDev built MiniCPM5-2B-Jev on OpenBMB’s MiniCPM5-2B, adapting it into a System 1 decision model.

📄 Give it a document and a set of questions. It returns probabilities for predefined options, without generating a free-form answer—helping developers:
- Classify requests and route support tickets
- Check whether conditions or requirements are met
- Score cases against defined criteria

📊 Results reported by the project:
🏆 78.79% on JevBench, ranking #1 among ≤2B open-weight System 1 / Jev models
✅ 86.41% accuracy on the 10-source decision-v7 benchmark
📏 0.0307 ECE on decision-v7, measuring how closely confidence matches accuracy

🛠️ Built for developers:
• Structured decision API via /v1/systemone
• Shared-context KV-cache reuse across multiple questions
• Open-source code, LoRA adapters, and calibration head under Apache 2.0
• Training and evaluation scripts to explore and reproduce the approach

From support-ticket routing to criteria-based scoring, this project shows how the community is adapting MiniCPM for practical decision workflows. 🌍

🙌 Shout-out to yuting-ai for building and sharing!

🔗 Explore Project: https://github.com/yuting-ai/minicpm5-2b-jev
🤗 Get MiniCPM5-2B: https://huggingface.co/openbmb/MiniCPM5-2B

#MiniCPM #OpenBMB #OpenSourceAI

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Original title: What if your model could make a structured choice instead of writing another paragraph? 🎯