ariannamethod/nanollama
📦 Open Source Projectariannamethod
A streamlined framework for training custom Llama 3 models from scratch at any scale.
nanollama provides a modular and educational codebase for training Llama 3 models from the ground up. By stripping away unnecessary complexity, it allows researchers and hobbyists to experiment with model architecture, parameter scaling, and personality fine-tuning without the overhead of massive enterprise frameworks. The repository includes utilities for handling transformer blocks, attention mechanisms, and the training loop, while maintaining compatibility with modern inference formats like GGUF. It serves as both a practical tool for custom model development and a pedagogical resource for those studying the internal workings of Llama-style architectures. Whether you are aiming to build a lightweight model for edge devices or exploring the nuances of transformer training, nanollama offers a clean, Python-centric environment to execute your experiments.
💡Highlights
- ├─Train Llama 3 from scratch
- ├─GGUF format compatibility
- └─Customizable model scaling
🎯For
- ├─AI Researchers
- ├─Machine Learning Engineers
- └─LLM Hobbyists