Palmyra x6 技术报告：锚定微调的企业智能体模型 Palmyra x6 Technical Report: An Agentic, Tool-Use Model Post-Trained via Anchored Supervised Fine-Tuning

精读摘要

这篇技术报告介绍了 Palmyra x6——基于混合专家（MoE）基座模型后训练得到的大语言模型，专门面向企业级智能体任务优化。训练方案刻意保守且可控：仅用 626 条经过验证的合成工具调用轨迹、单轮训练、低学习率，并以 KL 散度锚定冻结的基座模型，配合 Muon+Adam 混合优化器。结果显示该模型相比此前的默认模型有显著提升，说明精心筛选的少量数据同样能带来可观收益。 Palmyra x6 is an LLM optimized for enterprise agentic tasks, built by post-training a Mixture-of-Experts base model with Anchored Supervised Fine-Tuning. The recipe is deliberately conservative: 626 verified synthetic tool-use trajectories, a single epoch, a low learning rate, and a KL anchor to the frozen base, optimized with a Muon + Adam hybrid. It shows substantial gains over the previous default model.