LLMs-Zero-to-Hero is an open-source educational project designed to guide learners through the complete process of understanding and building large language models from the ground up. The repository presents a structured learning pathway that begins with fundamental concepts in machine learning and progresses toward advanced topics such as model pre-training, fine-tuning, and deployment. Rather than relying entirely on existing frameworks, the project encourages readers to implement important components themselves in order to gain a deeper understanding of how modern language models work internally. It includes explanations of dense transformer architectures, mixture-of-experts models, training pipelines, and techniques used in contemporary LLM development.
Features
- Step-by-step learning pathway for building large language models from scratch
- Hands-on implementation of transformer and mixture-of-experts architectures
- Tutorials covering pre-training, fine-tuning, and RLHF techniques
- Educational notebooks and code examples demonstrating model internals
- Integration with video tutorials and explanatory materials
- Coverage of deployment, inference optimization, and model scaling techniques