C5W3L03 Beam Search

(11:55)

How is Beam Search Really Implemented?

(8:15)

Confused which Transformer Architecture to use? BERT, GPT-3, T5, Chat GPT? Encoder Decoder Explained

(15:30)

ELI5 FlashAttention Algorithm and Online Normalizer Calculation for Softmax (NVIDIA Paper) - part 3

(44:25)

The KV Cache: Memory Usage in Transformers

(8:33)

Speculative Decoding: When Two LLMs are Faster than One

(12:46)

C5W3L04 Refining Beam Search

(11:1econd)

How a Transformer works at inference vs training time

(49:53)

LoRA: Low-Rank Adaptation of Large Language Models - Explained visually + PyTorch code from scratch

(26:55)

C5W3L07 Attention Model Intuition

(9:42)

C5W3L05 Error Analysis of Beam Search

(9:44)

Rotary Positional Embeddings: Combining Absolute and Relative

(11:17)