mksz1003-AI大模型微调，从原理剖析到企业级落地实战
https://cdn.ldstatic.com/images/emoji/twemoji/file_folder.png?v=15 mksz1003-AI大模型微调，从原理剖析到企业级落地实战https://cdn.ldstatic.com/images/emoji/twemoji/file_folder.png?v=15 第5章 微调医疗场景 Embedding 模型
https://cdn.ldstatic.com/images/emoji/twemoji/file_folder.png?v=15 第4章 Llama-Factory 微调实战
https://cdn.ldstatic.com/images/emoji/twemoji/file_folder.png?v=15 第1章 模型高效微调原理剖析
https://cdn.ldstatic.com/images/emoji/twemoji/file_folder.png?v=15 第9章 企业金融大模型微调项目—GRPO 方案设计与落地
https://cdn.ldstatic.com/images/emoji/twemoji/file_folder.png?v=15 第3章 大模型训练数据工程
https://cdn.ldstatic.com/images/emoji/twemoji/file_folder.png?v=15 第2章 大模型强化学习原理剖析
https://cdn.ldstatic.com/images/emoji/twemoji/file_folder.png?v=15 第7章 企业金融大模型微调项目—SFT 方案设计与落地
https://cdn.ldstatic.com/images/emoji/twemoji/file_folder.png?v=15 第6章 蒸馏专属大模型
https://cdn.ldstatic.com/images/emoji/twemoji/file_folder.png?v=15 第8章 企业金融大模型微调项目—奖励模型方案设计与落地
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 4-4 Llama-Factory微调之LoRa微调实战.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 4-10 Text2SQL模型微调之数据处理.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 4-9 Text2SQL模型微调之数据集准备.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 4-8 Text2SQL模型微调之数据集格式说明.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 4-3 Llama-Factory微调之模型和数据准备.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 4-12 Text2SQL模型微调之微调实战.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 4-15 Text2SQL模型微调之基于DeepSpeed实战.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 4-5 Llama-Factory微调之模型效果验证.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 4-11 Text2SQL模型微调之数据集注册.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 1-7 高效微调原理之预训练之网络通信.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 1-6 高效微调原理之预训练的两个挑战.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 1-3 高效微调原理之什么场景需要RAG？.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 1-10 高效微调原理之预训练之3D并行.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 1-12 高效微调原理之LoRA原理.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 1-8 高效微调原理之预训练之数据并行.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 1-9 高效微调原理之预训练之模型并行.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 1-5 高效微调原理之预训练的流程.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 1-11 高效微调原理之微调步骤.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 1-1 课程介绍.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 1-2 高效微调原理之什么场景需要微调？.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 1-4 高效微调原理之微调和全量微调的区别.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 5-12 Embedding模型微调之微调核心代码.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 5-7 Embedding模型微调之基础模型校验.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 5-11 Embedding模型微调之微调数据准备核心逻辑.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 5-5 Embedding模型微调之技术方案选型.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 5-6 Embedding模型微调之环境准备.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 5-4 Embedding模型微调之数据集准备.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 5-2 Embedding模型微调之适用场景剖析.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 5-13 Embedding模型微调之微调效果检验.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 5-9 Embedding模型微调之数据集清洗.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 5-8 Embedding模型微调之数据集校验.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 5-3 Embedding模型微调之基础模型选型.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 2-2 强化学习微调之什么是PPO？.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 2-3 强化学习微调之什么是RLHF？.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 2-1 强化学习微调之什么是强化学习？.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 2-4 强化学习微调之什么是DPO？.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 2-5 强化学习微调之什么是GRPO？.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 3-11 大模型微调数据集构建实操-构建偏好数据集.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 3-3 大模型微调预训练数据集.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 3-7 大模型微调数据集生成实战.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 3-4 大模型微调SFT数据集.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 3-5 大模型微调偏好数据集.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 3-8 大模型微调数据集工具部署.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 3-1 大模型微调数据的重要性.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 3-6 大模型微调COT数据集.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 3-9 大模型微调数据集构建实操-构建COT数据集.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 3-10 大模型微调数据集构建实操-构建SFT数据集.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 3-2 大模型微调数据格式划分.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 6-13 模型蒸馏之基于Llama-Factory进行全量微调.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 6-12 模型蒸馏之蒸馏数据集准备.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 6-3 模型蒸馏之为什么蒸馏方案突然火了起来？.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 6-6 模型蒸馏之全量微调工具推荐.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 6-10 模型蒸馏之蒸馏数据格式说明.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 6-4 模型蒸馏之模型推理能力的重要性.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 6-2 模型蒸馏之微调和全量微调的本质区别.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 6-14 模型蒸馏之模型蒸馏前后效果对比.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 6-9 模型蒸馏之全量微调工具安装部署.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 6-7 模型蒸馏之资源评估和服务器租赁.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 6-8 模型蒸馏之基础模型下载.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 6-11 模型蒸馏之基础模型效果测试.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 6-5 模型蒸馏之蒸馏流程剖析.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 6-1 模型蒸馏之蒸馏和微调的本质区别.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 7-30 SFT微调之LoRa微调-核心监控指标之eval_loss分析.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 7-29 SFT微调之LoRa微调-核心监控指标之train_loss分析.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 7-12 SFT 微调之 LoRa 微调 - 微调技术方案选型.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 7-15 SFT微调之LoRa微调-微调基座模型下载.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 7-36 SFT微调之LoRa微调-微调效果评估之评估效果说明.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 7-18 SFT微调之LoRa微调-LoRA参数配置.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 7-28 SFT微调之LoRa微调-TensorBoard可视化监控.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 7-5 SFT 微调之数据集选择.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 7-1 整体项目之项目背景.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 7-35 SFT微调之LoRa微调-微调效果评估之Perplexity指标.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 7-8 SFT 微调之数据集构建 - 数据集解析.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 7-32 SFT微调之LoRa微调-核心监控指标之grad_norm分析.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 7-31 SFT微调之LoRa微调-核心监控指标之learning_rate分析.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 7-3 整体项目之技术方案.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 7-34 SFT微调之LoRa微调-微调效果评估之ROUGE指标.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 7-23 SFT微调之LoRa微调-最佳模型保存函数.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 7-4 SFT 微调之微调技术流程.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 7-25 SFT微调之LoRa微调-模型微调的早停机制.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 7-26 SFT微调之LoRa微调-微调的checkpoints机制设置.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 7-11 SFT 微调之数据集构建 - 多轮数据集构建.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 7-17 SFT微调之LoRa微调-数据处理.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 7-20 SFT微调之LoRa微调-创建数据整理器.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 7-21 SFT微调之LoRa微调-基础模型加载.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 7-33 SFT微调之LoRa微调-多轮对话微调数据处理.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 7-24 SFT微调之LoRa微调-最后模型保存函数.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 7-6 SFT 微调之模型选型.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 7-10 SFT 微调之数据集构建 - 单轮数据集构建.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 7-19 SFT微调之LoRa微调-SFT微调参数配置.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 7-2 整体项目之项目需求.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 7-14 SFT微调之LoRa微调-微调环境构建.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 7-7 SFT 微调之微调方案选型.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 7-13 SFT微调之LoRa微调-微调技术方案设计思考.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 7-37 SFT微调之LoRa微调-微调效果评估之SFT模型部署.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 7-16 SFT微调之LoRa微调-数据样本初始化.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 7-22 SFT微调之LoRa微调-模型评估内存优化回调函数.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 7-9 SFT 微调之数据集构建 - 数据构建策略.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 8-8 奖励模型之奖励模型训练路径分析.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 8-6 奖励模型之微调数据集构建策略.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 8-9 奖励模型之基于RewardBench排行榜选型.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 8-10 奖励模型之奖励模型选型.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 8-2 奖励模型之为什么选GRPO？.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 8-1 奖励模型之需求背景分.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 8-4 奖励模型之整体流程设计.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 8-7 奖励模型之微调数据集构建脚本执行.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 8-5 奖励模型之微调数据集构建方案思考.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 8-3 奖励模型之为什么GRPO必须微调奖励模型？.mp4
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