1 repo
Awesome GitHub RepositoriesKnowledge Distillation
Techniques for transferring capabilities from large teacher models to smaller, more efficient student models.
Distinguishing note: Focuses on model compression and capability transfer rather than initial training.
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Awesome Knowledge Distillation GitHub Repositories
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- jingyaogong/minimind
jingyaogong/minimind
39,663View on GitHubThis project is a comprehensive framework for the entire lifecycle of transformer-based language models, supporting everything from foundational pretraining to specialized deployment. It provides a modular toolkit for defining neural network architectures, managing data preparation pipelines, and executing training routines across various scales. The framework is designed to handle the full model development process, including supervised fine-tuning, behavioral alignment, and the integration of agentic capabilities. What distinguishes this framework is its focus on efficient training and adva
The framework facilitates knowledge distillation by transferring capabilities from a large teacher model to a smaller student model using teacher-generated outputs to improve efficiency.
Pythonartificial-intelligencelarge-language-model
