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Awesome GitHub RepositoriesSparse Model Architectures
Architectural designs that activate only a subset of parameters per input to improve computational efficiency.
Distinguishing note: Focuses on conditional computation and routing mechanisms, distinct from dense model architectures.
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Awesome Sparse Model Architectures 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
Computational load is distributed across specialized sub-networks where only a subset of parameters is activated for each input token.
Pythonartificial-intelligencelarge-language-model
