【尊享】ZX114 – 大模型微调实战营 [31G]

【尊享】ZX114 – 大模型微调实战营 [31G]

┣━━01.视频 [30.8G]
┃ ┣━━第01周 [2.1G]
┃ ┃ ┗━━第一节 开营+大模型介绍、Transformer [2.1G]
┃ ┃ ┣━━第一课时-01开营.abc [382.9M]
┃ ┃ ┣━━第一课时-02大模型爆发式发展.abc [483.2M]
┃ ┃ ┣━━第一课时-03大模型是如何炼成的.abc [324.5M]
┃ ┃ ┣━━第一课时-04Transformer的应用.abc [377.6M]
┃ ┃ ┗━━第一课时-05Self-Attention.abc [591.4M]
┃ ┣━━第02周 [3G]
┃ ┃ ┗━━第二节 Transformer、Encoder、Advanced [3G]
┃ ┃ ┣━━水印 [434.6M]
┃ ┃ ┃ ┣━━第二课时-01Transformer Part1.abc [129.5M]
┃ ┃ ┃ ┣━━第二课时-02Transformer Part2.abc [160.8M]
┃ ┃ ┃ ┣━━第二课时-03Encoder-based and Decoder Based LLMs.abc [40.6M]
┃ ┃ ┃ ┗━━第二课时-04Advanced Topics.abc [103.8M]
┃ ┃ ┣━━第二课时-01Transformer Part1.abc [1.1G]
┃ ┃ ┣━━第二课时-02Transformer Part2.abc [766M]
┃ ┃ ┣━━第二课时-03Encoder-based and Decoder Based LLMs.abc [330.7M]
┃ ┃ ┗━━第二课时-04Advanced Topics.abc [454M]
┃ ┣━━第03周 [3.2G]
┃ ┃ ┗━━大模型微调概览 Lora微调 [3.2G]
┃ ┃ ┣━━水印 [573.8M]
┃ ┃ ┃ ┣━━第三课时-01大模型微调概览.abc [159.5M]
┃ ┃ ┃ ┣━━第三课时-02Lora微调-Lora算法.abc [157.4M]
┃ ┃ ┃ ┗━━第三课时-03Lora微调-从零实现Lora到Roberta.abc [256.8M]
┃ ┃ ┣━━第三课时-01大模型微调概览.abc [1.1G]
┃ ┃ ┣━━第三课时-02Lora微调-Lora算法.abc [1011.4M]
┃ ┃ ┗━━第三课时-03Lora微调-从零实现Lora到Roberta.abc [661M]
┃ ┣━━第04周 [3.4G]
┃ ┃ ┗━━Alpaca、AdaLoRA、QLoRA [3.4G]
┃ ┃ ┣━━第四课时-01Alpaca.abc [1.7G]
┃ ┃ ┣━━第四课时-02AdaLoRA.abc [1003M]
┃ ┃ ┗━━第四课时-03QLoRA.abc [748.5M]
┃ ┣━━第05周 [2.7G]
┃ ┃ ┗━━Prefix Tuning、Quantization [2.7G]
┃ ┃ ┣━━水印 [375.9M]
┃ ┃ ┃ ┣━━第五课时-01Prefix Tuning.abc [147.2M]
┃ ┃ ┃ ┣━━第五课时-02Quantization01.abc [81.3M]
┃ ┃ ┃ ┣━━第五课时-03Quantization02.abc [109.2M]
┃ ┃ ┃ ┗━━第五课时-04Quantization Methos for LLM.abc [38.2M]
┃ ┃ ┣━━第五课时-01Prefix Tuning.abc [1012.2M]
┃ ┃ ┣━━第五课时-02Quantization01.abc [562.2M]
┃ ┃ ┣━━第五课时-03Quantization02.abc [638.8M]
┃ ┃ ┗━━第五课时-04Quantization Methos for LLM.abc [214.2M]
┃ ┣━━第06周 [1.2G]
┃ ┃ ┗━━助教补课 llama介绍&运行&量化&部署&微调 [1.2G]
┃ ┃ ┣━━20240324 llama介绍&运行&量化&部署&微调01.abc [569.8M]
┃ ┃ ┗━━20240324 llama介绍&运行&量化&部署&微调02.abc [700.9M]
┃ ┣━━第07周 [2.1G]
┃ ┃ ┗━━Distributed Computing、Flash Attention [2.1G]
┃ ┃ ┣━━第六课时-01GPU时间计算.abc [574.1M]
┃ ┃ ┣━━第六课时-02 Distributed Computing.abc [449.3M]
┃ ┃ ┣━━第六课时-03ZeRO-123 and FSDP.abc [730.5M]
┃ ┃ ┗━━第六课时-04Flash Attention.abc [442M]
┃ ┣━━第08周 [2.8G]
┃ ┃ ┗━━Flash Attention cont、微调Mistral 7B [2.8G]
┃ ┃ ┣━━第六次课程补充课- 01Flash Attention cont.abc [545M]
┃ ┃ ┣━━第六次课程补充课-02Self-Attention的分块计算.abc [931.9M]
┃ ┃ ┣━━第六次课程补充课-03分块模式中计算O.abc [502.1M]
┃ ┃ ┣━━第六次课程补充课-04Mixture of Expert Model.abc [142.5M]
┃ ┃ ┗━━第六次课程补充课-05-微调Mistral 7B.abc [697.9M]
┃ ┣━━第09周 [2.7G]
┃ ┃ ┗━━强化学习 [2.7G]
┃ ┃ ┣━━第七课-01RLHF介绍.abc [918.8M]
┃ ┃ ┣━━第七课-02强化学习.abc [284.4M]
┃ ┃ ┣━━第七课-03Multi-armed Bandit.abc [619.2M]
┃ ┃ ┗━━第七课-04The goal of Agent.abc [930.3M]
┃ ┣━━第10周 [1.1G]
┃ ┃ ┣━━第七课-补充-01Optimal Policy.abc [716.8M]
┃ ┃ ┗━━第七课-补充-02Intro to Monte Carlo.abc [397.8M]
┃ ┣━━第11周 [2.4G]
┃ ┃ ┣━━第八课-01回顾Monte Carlo.abc [451M]
┃ ┃ ┣━━第八课-02PPO Algorithm.abc [469.1M]
┃ ┃ ┣━━第八课-03 from table to function approximation01.abc [641.7M]
┃ ┃ ┗━━第八课-04 from table to function approximation02.abc [943.9M]
┃ ┣━━第12周 [2.1G]
┃ ┃ ┣━━第九课-01REINFORCE-Monte Carlo Policy Gradient.abc [331.3M]
┃ ┃ ┣━━第九课-02 PPO01.abc [1G]
┃ ┃ ┗━━第九课-03 PPO02.abc [791.2M]
┃ ┗━━第13周 [1.8G]
┃ ┗━━项目MedicalGPT、DPO算法 [1.8G]
┃ ┣━━第九课-补充-01PPO回顾.abc [441.1M]
┃ ┣━━第九课-补充-02项目MedicalGPT.abc [1.1G]
┃ ┗━━第九课-补充-03DPO算法讲解.abc [365.4M]
┗━━00.资料.zip [196.1M]

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