Tokenization — Topic Summaries
AI-powered summaries of 6 videos about Tokenization.
6 summaries
Transformers, the tech behind LLMs | Deep Learning Chapter 5
Transformer-based models—behind systems like ChatGPT—turn text into a stream of vectors, mix information across tokens with attention, and then...
LSTM | Part 3 | Next Word Predictor Using | CampusX
A next word predictor can be built as a text generator, but it becomes much easier to train when the problem is reframed as supervised learning: turn...
LLM Foundations (LLM Bootcamp)
Large language models work because they turn text into numbers, then learn—via gradient-based training—to predict the next token using a Transformer...
Learn to Spell: Prompt Engineering (LLM Bootcamp)
Prompt engineering is the practical art of choosing the exact text you feed a language model so it behaves the way you need—often replacing what used...
AI Jargon, Demystified: 3 Concepts Everyone Misunderstands
AI’s biggest practical limits aren’t mysterious—they start with what data can actually be fed into a model, then show up as uneven “intelligence”...
Tiny Aya - Cohere's Mini Multilingual Models
Choosing a language model for non-English languages is often a guessing game—especially for low-resource languages with limited internet data and...