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Lecture 19: Birds Eye View of the LLM Architecture
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Building LLMs from scratch - Lecture 19: Birds Eye View of the LLM Architecture

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This course includes

  • 30.5 hours of video
  • Certificate of completion
  • Access on mobile and TV

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In this lecture, we start to learn about LLM architecture. This lecture provides you with a birds-eye view of how different LLM architecture components like token embeddings, transformer blocks, feedforward neural networks and the output layer interact with each other, for the next word prediction task. The key reference book which this video series very closely follows is Build a Large Language Model from Scratch by Manning Publications. All schematics and their descriptions are borrowed from this incredible book! This book serves as a comprehensive guide to understanding and building large language models, covering key concepts, techniques, and implementations. Affiliate links for purchasing the book will be added soon. Stay tuned for updates! 0:00 Goal of this lecture 3:37 Overview of the LLM architecture 11:34 GPT-2 model architecture overview 20:27 Begin coding the GPT-2 architecture 21:18 Dummy GPT model class 23:21 Passing the input 24:51 Vector embeddings 31:04 Positional embeddings 36:09 Transformer block 37:00 Output logits 43:00 LLM Architecture workflow summary 46:16 Next steps and recap Link to code file: https://drive.google.com/file/d/1k4TwMW6HHDiS1tcbGO5ip3zD3BonwSa0/view?usp=sharing ================================================= ✉️ Join our FREE Newsletter: https://vizuara.ai/our-newsletter/ ================================================= Vizuara philosophy: As we learn AI/ML/DL the material, we will share thoughts on what is actually useful in industry and what has become irrelevant. We will also share a lot of information on which subject contains open areas of research. Interested students can also start their research journey there. Students who are confused or stuck in their ML journey, maybe courses and offline videos are not inspiring enough. What might inspire you is if you see someone else learning and implementing machine learning from scratch. No cost. No hidden charges. Pure old school teaching and learning. ================================================= 🌟 Meet Our Team: 🌟 🎓 Dr. Raj Dandekar (MIT PhD, IIT Madras department topper) 🔗 LinkedIn: https://www.linkedin.com/in/raj-abhijit-dandekar-67a33118a/ 🎓 Dr. Rajat Dandekar (Purdue PhD, IIT Madras department gold medalist) 🔗 LinkedIn: https://www.linkedin.com/in/rajat-dandekar-901324b1/ 🎓 Dr. Sreedath Panat (MIT PhD, IIT Madras department gold medalist) 🔗 LinkedIn: https://www.linkedin.com/in/sreedath-panat-8a03b69a/ 🎓 Sahil Pocker (Machine Learning Engineer at Vizuara) 🔗 LinkedIn: https://www.linkedin.com/in/sahil-p-a7a30a8b/ 🎓 Abhijeet Singh (Software Developer at Vizuara, GSOC 24, SOB 23) 🔗 LinkedIn: https://www.linkedin.com/in/abhijeet-singh-9a1881192/ 🎓 Sourav Jana (Software Developer at Vizuara) 🔗 LinkedIn: https://www.linkedin.com/in/souravjana131/

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