Learn LLMs
I’ve spent the last 15+ years working in genomics, and I see myself as an infinite learner. My background demands verifiable data and scientific rigor, while my curiosity drives me to explore new frontiers. This is my journey applying both to understand the architecture behind Large Language Models (LLMs) and agentic systems.
I’m not here for the AI-HaaS (“hype as a service”) wave. I’m here to understand the core technologies that make these systems work from the inside out. This learning hub is my technical journal —a public space where I collect, organize, and clarify my discoveries about LLMs and the ecosystem being built around them.
Building Blocks of GPT-2 LLM
- Introduction - Building Blocks of GPT-2 LLM
- Introduction to Large Language Models (LLMs)
- GPT - Generative Pretrained Transformer model
- Introduction to tokenization
- Introduction to embedding
- Transformer blocks
- Self-attention mechanism
- Masked Attention
- Multi-head self-attention
- Feedforward neural network (FNN)
- Language Modeling Head (LM Head)
- Pre-trained GPT-2 model end to end
- Dataflow across LLM
- Reference
Architecting Autonomous Systems