《李宏毅深度学习教程》（李宏毅老师推荐👍，苹果书🍎），PDF下载地址：https://github.com/datawhalechina/leedl-tutorial/releases

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• Updated Oct 23, 2026
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[CVPR 2023] DepGraph: Towards Any Structural Pruning; LLMs, Vision Foundation Models, etc.

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• Updated Sep 7, 2025
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Sparsity-aware deep learning inference runtime for CPUs

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• Updated Jun 2, 2025
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AIMET is a library that provides advanced quantization and compression techniques for trained neural network models.

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• Updated Nov 12, 2026
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SOTA low-bit LLM quantization (INT8/FP8/MXFP8/INT4/MXFP4/NVFP4) & sparsity; leading model compression techniques on PyTorch, TensorFlow, and ONNX Runtime

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• Updated Nov 12, 2026
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A curated list of neural network pruning resources.

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• Updated Apr 4, 2024

micronet, a model compression and deploy lib. compression: 1、quantization: quantization-aware-training(QAT), High-Bit(>2b)(DoReFa/Quantization and Training of Neural Networks for Efficient Integer-Arithmetic-Only Inference)、Low-Bit(≤2b)/Ternary and Binary(TWN/BNN/XNOR-Net); post-training-quantization(PTQ), 8-bit(tensorrt); 2、 pruning: normal、reg…

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• Updated May 6, 2025
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Libraries for applying sparsification recipes to neural networks with a few lines of code, enabling faster and smaller models

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• Updated Jun 2, 2025
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Config driven, easy backup cli for restic.

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• Updated Apr 5, 2026
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Practical course about Large Language Models.

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• Updated Sep 29, 2026
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OpenMMLab Model Compression Toolbox and Benchmark.

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• Updated Jun 11, 2024
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PaddleSlim is an open-source library for deep model compression and architecture search.

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• Updated Jan 4, 2026
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A toolkit to optimize ML models for deployment for Keras and TensorFlow, including quantization and pruning.

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• Updated Nov 11, 2026
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Efficient computing methods developed by Huawei Noah's Ark Lab

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• Updated Nov 5, 2024
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Neural Network Compression Framework for enhanced OpenVINO™ inference

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• Updated Nov 9, 2026
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[NeurIPS 2023] LLM-Pruner: On the Structural Pruning of Large Language Models. Support Llama-3/3.1, Llama-2, LLaMA, BLOOM, Vicuna, Baichuan, TinyLlama, etc.

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• Updated Oct 7, 2024
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PyTorch Implementation of [1611.06440] Pruning Convolutional Neural Networks for Resource Efficient Inference

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• Updated Jul 12, 2019
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TinyNeuralNetwork is an efficient and easy-to-use deep learning model compression framework.

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• Updated Mar 3, 2026
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mobilev2-yolov5s剪枝、蒸馏，支持ncnn，tensorRT部署。ultra-light but better performence！

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• Updated Sep 26, 2022
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Embedded and mobile deep learning research resources

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• Updated Mar 14, 2023