- 对机器学习和深度学习的基本理解
- 具有Python编程经验
- 熟悉自然语言处理(NLP)概念
观众
- AI研究人员
- 数据科学家
- Machine Learning工程师
- 对NLP感兴趣的软件开发人员
Large Language Models (LLMs)由Meta AI开发，是能够理解和生成类人文本的强大深度学习模型。这些模型广泛应用于聊天机器人、文本摘要、情绪分析和内容生成等应用。
这个由讲师主导的现场培训（在线或现场）旨在让中级到高级的AI研究人员、数据科学家和开发人员了解、微调和实施Meta AI的大型语言模型，以便为各种NLP应用程序服务。
参加培训结束时，参加者将能够：
- 了解Meta AI的大型语言模型的架构和功能。
- 针对特定用例设置和微调Meta AI LLM。
- 实施基于LLM的应用程序，如文本摘要、聊天机器人和情绪分析。
- 高效优化和部署大型语言模型。
课程形式
- 互动讲座和讨论。
- 大量的练习和实践。
- 在实时实验室环境中进行动手实施。
课程定制选项
- 要请求此课程的定制培训，请联系我们进行安排。
大型语言模型介绍
- Natural Language Processing (NLP)概述
- Large Language Models (LLMs)介绍
- Meta AI对LLM开发的贡献
了解Meta AI LLM的架构
- Transformer架构和自我注意力机制
- 大规模模型的训练方法
- 与其他LLM(GPT、BERT、T5等)的比较
设置开发环境
- 安装和配置Python和Jupyter Notebook
- 使用Hugging Face和Meta AI的模型库
- 使用基于云或本地的GPU进行训练
加载Fine-Tuning和自定义Meta AI LLM
- 加载预训练模型
- 在特定领域数据集上进行微调
- 迁移学习技术
用Meta AI LLM构建NLP应用程序
- 开发聊天机器人和对话AI
- 实现文本总结和改写
- 情感分析和内容审核
优化和部署大型语言模型
- 推理速度的性能调优
- 模型压缩和量化技术
- 使用API和云平台部署LLM
伦理考虑和负责任的AI
- LLM中的偏见检测和减轻
- 确保AI模型的透明度和公平性
- AI的未来趋势和发展
总结和结论
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