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Supervised FinetuningDuring supervised fine-tuning, the model is trained on a large corpus of high-quality prompts curated for difficulty, quality, and domain diversity. Prompts are sourced from open datasets and labeled using custom models to identify domains and analyze distribution coverage. To address gaps in underrepresented or low-difficulty areas, additional prompts are synthetically generated based on the pre-training domain mixture. Empirical analysis showed that most publicly available datasets are dominated by low-quality, homogeneous, and easy prompts, which limits continued learning. To mitigate this, we invested significant effort in building high-quality prompts across domains. All corresponding completions are produced internally and passed through rigorous quality filtering. The dataset also includes extensive agentic traces generated from both simulated environments and real-world repositories, enabling the model to learn tool interaction, environment reasoning, and multi-step decision making.
。关于这个话题，新收录的资料提供了深入分析
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Don’t buy one unless you can see the “EX” label on the card and package. | Image: Cameron Faulkner / The Verge
，详情可参考新收录的资料
Отправка американских военнослужащих в Иран возможна. Об этом заявил президент Соединенных Штатов Дональд Трамп во время общения с журналистами.。新收录的资料是该领域的重要参考
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