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Open-source Cleo model integrates analyst behavior into 2B parameters

A new open-source project named Cleo has been developed, aiming to integrate full analyst behavior into a small, 2-billion parameter model. This project fine-tunes a Qwen3.5-2B-Base model and emphasizes a unified harness for training, evaluation, and inference. Key features include training on data preparation and answering contracts, searching queries with live execution evidence, and co-designing the model's safety, SQL handling, and clarification behaviors as a single system. All components, including the harness, model, and datasets, are publicly available. AI

IMPACT This project demonstrates the feasibility of integrating complex analyst behaviors into smaller models, potentially enabling more efficient and accessible AI solutions for data analysis tasks.

RANK_REASON The cluster describes the release of an open-source model and associated datasets and harness, fitting the research bucket. [lever_c_demoted from research: ic=1 ai=1.0]

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COVERAGE [1]

  1. r/MachineLearning TIER_1 English(EN) · /u/Dreeseaw ·

    Cleo: trying to fit full analyst behavior in a 2B model [P]

    <!-- SC_OFF --><div class="md"><p>Hello all! </p> <p>Half of all industrial &quot;chatbots&quot; are just text-to-SQL models in a trenchcoat (and the other half RAG!). I wanted to explore just how small you could make these models if you trained, evaluated, and ran inference in t…