Full Stack LLM Bootcamp (Free)

LLM에 관심있는 분들은 참고하시기 바랍니다. fullstackdeeplearning에서 올해 초 진행한 LLM Bootcamp 내용입니다. 각 세션마다 유튜브영상과 슬라이드 자료를 공개하고 있으니 참고하시기 바랍니다. 1. Learn to Spell: Prompt Engineering -- https://fullstackdeeplearning.com/llm-bootcamp/spring-2023/prompt-engineering/ * High-level intuitions for prompting * Tips and tricks for effective prompting: decomposition/chain-of-thought, self-criticism, ensembling * Gotchas: "few-shot learning" and tokenization 2. LLMOps -- https://fullstackdeeplearning.com/llm-bootcamp/spring-2023/llmops/ * Comparing and evaluating open source and proprietary models * Iteration and prompt management * Applying test-driven-development and continuous integration to LLMs 3. UX for Language User Interfaces -- https://fullstackdeeplearning.com/llm-bootcamp/spring-2023/ux-for-luis/ * General principles for user-centered design * Emerging patterns in UX design for LUIs * UX case studies: GitHub Copilot and Bing Chat 4. Augmented Language Models -- https://fullstackdeeplearning.com/llm-bootcamp/spring-2023/augmented-language-models/ * Augmenting language model inputs with external knowledge * Vector indices and embedding management systems * Augmenting language model outputs with external tools 5. Launch an LLM App in One Hour -- https://fullstackdeeplearning.com/llm-bootcamp/spring-2023/launch-an-llm-app-in-one-hour/ * Why is now the right time to build? * Techniques and tools for the tinkering and discovery phase: ChatGPT, LangChain, Colab * A simple stack for quickly launching augmented LLM applications 6. LLM Foundations -- https://fullstackdeeplearning.com/llm-bootcamp/spring-2023/llm-foundations/ * Speed-run of ML fundamentals * The Transformer architecture * Notable LLMs and their datasets 7. Project Walkthrough: askFSDL -- https://fullstackdeeplearning.com/llm-bootcamp/spring-2023/askfsdl-walkthrough/ * Walkthrough of a GitHub repo for sourced Q&A with LLMs * Try it out via a bot in our Discord * Python project tooling, ETL/data processing, deployment on Modal, and monitoring with Gantry * 8. What's Next? -- https://fullstackdeeplearning.com/llm-bootcamp/spring-2023/whats-next/ * Can we build general purpose robots using multimodal models? * Will models get bigger or smaller? Are we running out of data? * How close are we to AGI? Can we make it safe? 9. Reza Shabani: How To Train Your Own LLM -- https://fullstackdeeplearning.com/llm-bootcamp/spring-2023/shabani-train-your-own/ * The "Modern LLM Stack": Databricks, Hugging Face, MosaicML, and more * The importance of knowing your data and designing preprocessing carefully * The features of a good LLM engineer * By Reza Shabani, who trained Replit's code completion model, Ghostwriter. 10. Harrison Chase: Agents -- https://fullstackdeeplearning.com/llm-bootcamp/spring-2023/chase-agents/ * The "agent" design pattern: tool use, memory, reflection, and goals * Challenges facing agents in production: controlling tool use, parsing outputs, handling large contexts, and more * Exciting research projects with agents: AutoGPT, BabyAGI, CAMEL, and Generative Agents * By Harrison Chase, co-creator of LangChain 11. Fireside Chat with Peter Welinder -- https://fullstackdeeplearning.com/llm-bootcamp/spring-2023/welinder-fireside-chat/ * With Peter Welinder, VP of Product & Partnerships at OpenAI * How OpenAI converged on LLMs * Learnings and surprises from releasing ChatGPT