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ai deep-dive Reading Stanford CS224N

CS224N Lecture 9: Prompting, LoRA, and Parameter-Efficient Adaptation

Lecture 9 compares prompting, pruning, LoRA, prompt tuning, and adapters. Each asks the same question: how many parameters must change, and how much task-specific state must be stored, to adapt a large pretrained model?

#cs224n#peft#lora#prompting#stanford
learning guide Berkeley CS288 Spring 2026

Berkeley CS288 Part 3: Pre-training, Post-training, Generation, and Evaluation

Units 08–12 turn a base model into an interactive system: pre-training establishes capability, post-training shapes behavior, and generation plus evaluation determine how outputs are used.

#berkeley#cs288#llm#post-training#evaluation#prompting