RoPE (Rotary positional embeddings) explained: The positional workhorse of modern LLMs
11:17
Rotary Positional Embeddings: Combining Absolute and Relative
13:39
How Rotary Position Embedding Supercharges Modern LLMs
1:10:55
LLaMA explained: KV-Cache, Rotary Positional Embedding, RMS Norm, Grouped Query Attention, SwiGLU
22:43
How might LLMs store facts | DL7
23:26
Rotary Position Embedding explained deeply (w/ code)
36:16
The math behind Attention: Keys, Queries, and Values matrices
32:31
Round and Round We Go! What makes Rotary Positional Encodings useful?
57:45