The Full Stack - Learn to Spell: Prompt Engineering
Fullstackdeeplearning
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
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2023년 11월 8일 오전 7:57
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