Complete DSPy Tutorial - Master LLM Prompt Programming in 8 amazing examples!

In this video, we talk about Stanford NLP's DSPy - a new LLM Programming framework that helps with prompting, bootstrapping, optimizing, and fine-tuning Language Models. We go through 8 examples that step by step explain the major concepts behind DSPy and how to build really complex LLM programs with just a few lines of code! Let's build programs with both LLMs (like ChatGPT, Mixtral, Gemini, LLama-3) as well as local models (like T5, LLama, GPT-1 etc)! #ai #promptengineering #python Give me a follow on Twitter for regular channel updates + daily ML/AI tutorials: https://x.com/neural_avb Around 7:00, there used to be a clip from the world cup 2014 finals, but I removed it because FIFA wanted to copyright it lol. Patrons will get access to write-ups, slides, notebooks, and bonus content from all videos on my channel! Please consider supporting us coz it helps the channel massively! Patreon post link:   / access-to-dspy-109759018   If you enjoy what I do, consider buying me a coffee! Every little bit means the world! https://ko-fi.com/neuralavb Visit my Patreon link to see what else is available:   / neuralbreakdownwithavb   AI Agent Store link: https://aiagentstore.ai/?ref=avishek TextGrad tutorial:    • The complete TextGrad Tutorial - Easily op...   Links: DSPy Page: https://dspy-docs.vercel.app/docs/intro How to Setup DSPy: https://github.com/stanfordnlp/dspy?t... Intro DSPy Notebook: https://github.com/stanfordnlp/dspy/b... Videos you may like: The Full History of NLP Explained -    • 10 years of NLP history explained in 50 co...   Attention to Transformers Playlist -    • Attention to Transformers from zero to her...   Timestamps: 0:00 - Intro 0:47 - Prompt Programming vs Engineering 3:14 - Example 1 - Basic QA 6:20 - Example 2 - Chain of Thought 11:43 - Example 3 - Predicting floats, bools, JSON 14:14 - Example 4 - Retrieval Augmented Generation (RAG) 17:49 - Example 5 - Multi Hop 20:33 - Example 6 - Optimizers and Few Shot Prompts 23:54 - Example 6b - Assert and Suggest 25:46 - Example 7 - Generating Datasets 27:35 - Example 8 - Finetune a T5 model with ChatGPT 33:45 - Outro