Similar Tracks
Which transformer architecture is best? Encoder-only vs Encoder-decoder vs Decoder-only models
Efficient NLP
LLaMA explained: KV-Cache, Rotary Positional Embedding, RMS Norm, Grouped Query Attention, SwiGLU
Umar Jamil
RoPE (Rotary positional embeddings) explained: The positional workhorse of modern LLMs
DeepLearning Hero
Evolution of the Transformer architecture 2017–2025 | Comparing positional encoding methods
3CodeCamp
Attention is all you need (Transformer) - Model explanation (including math), Inference and Training
Umar Jamil