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Awesome GitHub RepositoriesArchitecture Definitions
Standardized components and configurations for building transformer-based neural networks.
Distinguishing note: Focuses on the specific building blocks of architectures like layers and activation functions.
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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 supports the definition of transformer-based architectures, including dense or mixture-of-experts layers, with standard components like normalization, activation functions, and positional embeddings.
Pythonartificial-intelligencelarge-language-model
