Building production LLM and NLP systems: retrieval, semantic search, embeddings, and agents that run at scale, not in a notebook.
Implementation notes and articles on LLM architecture, attention mechanisms, PyTorch, semantic search, vector embeddings, text processing, and production NLP systems.
Understanding why we use negative infinity instead of zero for masking in transformer attention mechanisms. Learn about causal...
Learn about Unicode normalization, non-breaking spaces (\xa0), and how to handle text encoding issues in Python. Understand NFC,...