Rotary Positional Embeddings: Combining Absolute and Relative
7:38
Which transformer architecture is best? Encoder-only vs Encoder-decoder vs Decoder-only models
45:12
LLM8 Language Modeling 2
12:30
DPO Explained: Enhancing LLM Training the Smart Way
8:33
The KV Cache: Memory Usage in Transformers
14:06
RoPE (Rotary positional embeddings) explained: The positional workhorse of modern LLMs
13:39
How Rotary Position Embedding Supercharges Modern LLMs
19:29
Positional encodings in transformers (NLP817 11.5)
23:26