Awesome GitHub RepositoriesInstruction Fine-Tuning Frameworks

This project provides an end-to-end framework for adapting large language models to follow user instructions through supervised fine-tuning. It functions as a comprehensive training pipeline that enables the creation of specialized assistant models by minimizing the difference between predicted outputs and target responses within structured instruction datasets. The framework distinguishes itself by integrating synthetic data generation with memory-efficient training techniques. It utilizes powerful language models to iteratively expand small sets of human-written seeds into diverse, high-qua

Train a language model using supervised learning on instruction demonstrations generated by a larger model to create a cost-effective and capable assistant.