transformers advanced
Attention Variants Compared: MHA, MQA, GQA, and MLA
Technical comparison of Multi-Head Attention, Multi-Query Attention, Grouped-Query Attention, and Multi-head Latent Attention. Analysis of memory-compute trade-offs and implementation considerations.
transformers advanced
Grouped Query Attention: Memory-Throughput Trade-offs
Analysis of GQA's KV cache reduction mechanism, optimal group sizes, and performance implications for inference at scale. Includes benchmarks across different model sizes.
transformers advanced
RoPE Embeddings: Implementation and Long Context Scaling
Understanding Rotary Position Embeddings, their efficient implementation, and techniques for extending context length including YaRN and Dynamic NTK scaling.