Building LLMs from scratch - Dataloaders in LLM Classification Finetuning | Python Coding | Hands on LLM project

In this lecture, we continue making progress in the LLM Classification finetuning project. We learn about datasets and dataloaders. Finally, we implement dataloaders for the training, testing and validation datasets to efficiently manage the data. 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 Recap of classification finetuning 3:33 Datasets and Dataloaders introduction 5:54 Equal text length for all data samples 8:26 End of text padding 13:02 Coding the Spam Dataset class in Python 22:50 Coding the Data Loaders 29:44 Recap and next steps Email classification dataset: https://archive.ics.uci.edu/dataset/228/sms+spam+collection PyTorch Datasets and Dataloaders: https://pytorch.org/tutorials/beginner/basics/data_tutorial.html OpenAI Tiktoken library: https://github.com/openai/tiktoken ================================================= ✉️ 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/