文件内容:
file:26_26Embedding文本向量化处理实战.mp4
file:25_25SentenceTransformer大模型详解.mp4
file:30_30使用Streamlit创建Web应用实战.mp4
file:35_35Indexing.mp4
file:12_12向量数据库选型.mp4
file:36_36检索和生成.mp4
file:2_2大模型目前固有的局限性.mp4
file:30_30使用Streamlit创建Web应用实战_20250315_224845.mp4
file:38_38增量训练pretrainging.mp4
file:7_7什么是向量.mp4
file:19_19PDF文档表格处理.mp4
file:29_29使用Llamalndex创建知识库实战.mp4
file:33_33大模型的局限性及解决方案.mp4
file:10_10VectorStore向量存储与检索.mp4
file:1、RAG工作原理.mp4
file:9_9文本向量是怎么得到的选.mp4
file:32_32实战二什么叫预训练好的大模型.mp4
file:6_6Prompt模版.mp4
file:22_22RAGVSFineTuning模型微调.mp4
file:34_34rag外挂私有知识库.mp4
file:21_21实战一RAGWorkflowI作流详解.mp4
file:8_8文本向量.mp4
file:15_15检索后排序.mp4
file:39_39functioncalling调用企业.mp4
file:27_27InternLM218BQwen25I05B模型实战.mp4
file:14_14文本分割粒度.mp4
file:28_28知识库模型问答测试与实际效果评估.mp4
file:23_23大模型企业级业务场景落地方案实践.mp4
file:18_18RRF.mp4
file:37_37finetuning微调.mp4
folder:225830_【教程】大模型RAG入门到精通：2025最新实战教程