LLMs from Scratch – Practical Engineering from Base Model to PPO RLHF
This comprehensive course guides learners through building a large language model from scratch using PyTorch, covering foundational concepts, advanced techniques, and alignment with reinforcement learning from human feedback.
MAIN POINTS FROM TRANSCRIPT
- Implement core transformer architecture and train a tiny language model using PyTorch.
- Modernize and scale the model with enhancements like mixture of experts layers and mixed precision training.
- Transition to full alignment with supervised fine-tuning and reward modeling.
- Complete the life cycle using proximal policy optimization for reinforcement learning from human feedback.
TAKEAWAYS
- Gain deep hands-on experience in building and customizing large language models.
- Understand the building blocks of models like GPT through practical implementation.
- Course setup requires only a laptop with Python and PyTorch, GPU is optional.
- Structured learning from foundational transformer concepts to advanced model scaling and alignment techniques.