Build a Large Language Model (From Scratch) - Sebastian Raschka
- Plan and code all the parts of an LLM
- Prepare a dataset suitable for LLM training
- Fine-tune LLMs for text classification and with your own data
- Use human feedback to ensure your LLM follows instructions
- Load pretrained weights into an LLM
- Implement core reasoning improvements for LLMs
- Evaluate models using judgment-based and benchmark-based methods
- Improve reasoning without updating model weights
- Use reinforcement learning to integrate external tools like calculators
- Apply distillation techniques to learn from larger reasoning models
- Understand the full reasoning model development pipeline
