English(EN) Improve your agent’s tool-calling accuracy with SFT and DPO on Amazon SageMaker AI

AWS SageMaker AI 通过 SFT 和 DPO 增强代理工具调用

作者 PulseAugur 编辑部 · [2 个来源] · 2026-06-03 15:56

Amazon SageMaker AI 现在提供了一种提高 AI 代理工具调用准确性的方法。这是通过采用监督微调 (SFT) 和直接偏好优化 (DPO) 技术来实现的。该过程涉及使用精选数据集和人类反馈来训练小型语言模型 (SLM)，以提高其为任务选择正确工具的能力。 AI

影响增强了 AI 代理的可靠性和效率，有可能降低部署代理应用程序的企业的运营成本。

排序理由文章描述了一种在现有平台上改进 AI 代理功能的新方法，而不是发布新模型。

AI 生成摘要 · Google Gemini · 来自 2 个来源。我们如何撰写摘要 →

报道来源 [2]

AWS Machine Learning Blog TIER_1 English(EN) · Amin Dashti · 2026-06-03 15:56

Improve your agent’s tool-calling accuracy with SFT and DPO on Amazon SageMaker AI

In this post, you learn how to use Supervised Fine-Tuning (SFT) and Direct Preference Optimization (DPO) together to improve the tool-calling accuracy of a small language model (SLM). The example uses Amazon SageMaker AI training jobs, so you can focus on training code instead of…
Mastodon — fosstodon.org TIER_1 English(EN) · [email protected] · 2026-06-03 16:01

🤖 Improve your agent’s tool-calling accuracy with SFT and DPO on Amazon SageMaker AI In this post, you learn how to use Supervised Fine-Tuning (SFT) and Direct

🤖 Improve your agent’s tool-calling accuracy with SFT and DPO on Amazon SageMaker AI In this post, you learn how to use Supervised Fine-Tuning (SFT) and Direct Preference Optimization (DPO) together to improve the tool-calling accuracy of a small language model (SLM). The example…

链接 aws.amazon.com/…/improve-your-agents-tool…