This is The most comprehensive prompt hacking course available, which record our progress on a prompt engineering and prompt hacking course.
从0开始大模型开发与微调|基于PyTorch与ChatGLM|PyTorch2.0深度学习环境搭建|从0学习深度学习|基础算法详解|神经网络|梯度下降|基于PyTorch卷积层的MNIST实战|可视化PyTorch数据处理和模型展示|RestNet实战|词嵌入|基于循环神经网络的中文情感分类|NLP编码器|预训练模型BERT|从1开始的NLP解码器|强化学习实战|ChatGLM使用详解高级微调|定制化应用|使用详解|训练自己的ChatGPT|只具有解码器的GPT2模型|基于加速库Accelerator的全量数据微调|基于Lora的模型微调|基于Huggingface的PERT模型微调
第17 章 开源大模型ChatGLM高级定制化应用实战|医疗问答GLMQABot搭建实战|基于ChatGLM搭建专业客服机器人||金融信息抽取实战-基于知识链的ChatGLM本地化知识库检索和智能答案生成|
We compare traditional tools with LLM-based tools to evaluate their effectiveness in data analytics education for non-computational professionals and students. Our approach, validated through two case studies, shows that using generative AI as the primary tool significantly improves learning efficiency and project development speed.
This repository include all of my LLMs learning codes.
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