tl;dr: This lecture discusses prompt-based learning as an alternative to fine-tuning LLMs, exploring how different prompt types influence model performance and sensitivity. It covers discrete and continuous prompting methods, highlighting their challenges, optimizations, and the role of prompt tuning in improving task adaptability.
🎓 Lecturer: Tanmoy Chakraborty [https://tanmoychak.com]
🔗 Get the Book: https://tanmoychak.com/llmbook
📚 Suggested Readings:
- Chapter-9, Intro to LLM, Sections 9.1 (Prompt Engineering), 9.2 (Prompt Application) [https://tanmoychak.com/llmbook]"
