開源模型逆襲：Databricks TAO 技術微調 Llama 超越 GPT-4o
近日，數據智能公司 Databricks 推出了一種全新的大語言模型微調方法 ——TAO（Test-time Adaptive Optimization），這一技術的出現爲開源模型的發展帶來了新的希望。通過運用無標註數據和強化學習，TAO 不僅在降低企業成本方面表現出色，更是在一系列基準測試中取得了令人矚目的成績。根據科技媒體 NeoWin 的報道，TAO 微調後的 Llama3.370B 模型在金融文檔問答和 SQL 生成等任務中，展現出了優於傳統標註微調方法的性能，甚至逼近了 OpenAI 的頂級閉源模型。這一成果標誌着開源模型在與商用 AI 產品
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