Building production LLM and NLP systems: retrieval, semantic search, embeddings, and agents that run at scale, not in a notebook.
Lessons from HuggingFace's FineWeb 15T-token recipe: base filtering, why more deduplication can hurt, C4 filters, and how FineWeb-Edu...
Guarantee an LLM only emits labels from your taxonomy: mask invalid logits to negative infinity and drive the...
How Gemma 3 got faster and leaner: SigLIP over CLIP, 128K context by interleaving, grouped-query attention, QK-Norm, and...
A deep dive into the LLaMA 2 architecture, explaining pretraining details, fine-tuning processes, Grouped-Query Attention, and Ghost Attention mechanisms.
A detailed breakdown of Key-Value (KV) caching in transformer models, detailing how it optimizes sequence generation speed by saving key and value tensors.
Learn how PagedAttention, the core technology behind vLLM, manages KV cache memory layout dynamically to reduce fragmentation and scale concurrent LLM serving.