电商客服 AI：构建微调支持模型
用基于工单历史训练的微调模型替换昂贵的 GPT-4 支持调用。以下是完整构建：数据准备、训练、部署和准确率目标。
每月处理 8,000 张支持工单的电商品牌使用 GPT-4 大约花费 $3,000-5,000/月的 API 成本。基于其工单历史训练的微调模型每月基础设施成本 $20，以更高的品牌特定问题准确率处理相同量。
第 1 步：提取和清洗训练数据
从工单系统导出过去 12-18 个月的已解决工单。目标数据集：1,000-3,000 个干净的（工单，解决方案）对。
第 2 步：构建 JSONL 数据集
在系统消息中包含当前政策。包含升级示例。
第 3 步：使用 Ertas 训练
基础模型：Llama 3 8B Instruct。训练时间约 45-75 分钟。
第 4 步：评估
目标：80%+ 评分为 3（正确），低于 5% 评分为 1（错误）。
第 5 步：部署 和路由
Ollama 在专用 VPS 上。从 1-click 批准模式开始，在 3 个月内达到 60-70% 完全自动化。
持续维护
每月审查被编辑或拒绝的自动响应。编辑就是新的训练数据。每季度重新训练。
Ship AI that runs on your users' devices.
Ertas early bird pricing starts at $14.50/mo — locked in for life. Plans for builders and agencies.
延伸阅读
Ship AI that runs on your users' devices.
Early bird pricing starts at $14.50/mo — locked in for life. Plans for builders and agencies.
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