A Visual Guide to Attention Variants in Modern LLMs
A visual guide to attention variants in modern LLMs, covering MHA, GQA, MLA, sparse attention, and hybrid architectures.
A visual guide to attention variants in modern LLMs, covering MHA, GQA, MLA, sparse attention, and hybrid architectures.
A technical deep dive into DeepSeek's Multi-Head Latent Attention mechanism, covering its mathematics and implementation in Julia.
A tutorial on coding self-attention, multi-head attention, causal attention, and cross-attention in LLMs using Python and PyTorch.
A tutorial on coding self-attention, multi-head attention, causal attention, and cross-attention in LLMs using Python and PyTorch.