Rotary Positional Embeddings: Combining Absolute and Relative
7:38
Which transformer architecture is best? Encoder-only vs Encoder-decoder vs Decoder-only models
1:10:55
LLaMA explained: KV-Cache, Rotary Positional Embedding, RMS Norm, Grouped Query Attention, SwiGLU
13:39
How Rotary Position Embedding Supercharges Modern LLMs
48:34
Customer Journey Optimisation with Vicky Lewis
29:38
Formation LLM pour jouer aux échecs en utilisant l'apprentissage par renforcement Deepseek GRPO
8:33
The KV Cache: Memory Usage in Transformers
23:26
Rotary Position Embedding explained deeply (w/ code)
12:47