This tutorial offers a detailed, line-by-line PyTorch implementation of the Transformer model introduced in "Attention Is All You Need." It elucidates the model's architecture—comprising encoder-decoder structures with multi-head self-attention and feed-forward layers—enhancing understanding through annotated code and explanations. This resource serves as both an educational tool and a practical guide for implementing and comprehending Transformer-based models.
The best introduction to how large language models (LLMs) like ChatGPT works in the world. It covers the three main stages of their training: pre-training on vast amounts of internet text, supervised fine-tuning to become helpful assistants, and reinforcement learning to improve problem-solving skills. The video also discusses LLM psychology, including why they hallucinate, how they use tools, and their limitations. Finally, it looks at future capabilities like multimodality and agent-like behavior.
The best introduction on how to use LLMs like ChatGPT. It covers the basics of how LLMs work, including concepts like "tokens" and "context windows". The video then demonstrates practical applications, such as using LLMs for knowledge-based queries, and more advanced features like "thinking models" for complex reasoning. It also explores how LLMs can use external tools for internet searches and deep research. Finally, the video delves into the multimodal capabilities of LLMs, including their use of voice, images, and video.
