Shypd.aiThe largest open index of AI toolsmmrazor is an OpenMMLab model compression toolbox and benchmark that provides tools for neural architecture search, pruning, knowledge distillation, and quantization. It helps developers slim down and optimize deep learning models.
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mmrazor is a comprehensive model compression toolkit and benchmark developed as part of the OpenMMLab project. It offers four mainstream technologies: Neural Architecture Search (NAS), Pruning, Knowledge Distillation (KD), and Quantization. Designed for flexibility and compatibility, mmrazor can be easily integrated with various OpenMMLab projects and allows for plug-n-play incorporation of different algorithms. Its modular design enables developers to implement new model compression algorithms with minimal code or by modifying configuration files. The toolbox supports a wide range of algorithms within each category, including DARTS, DetNAS, SPOS for NAS; AutoSlim, L1-norm, Group Fisher, DMCP for pruning; and various methods like CWD, WSLD, ABLoss for KD. It also includes PTQ, QAT, and LSQ for quantization, making it a versatile tool for optimizing deep learning models.
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