Keras model compressionModel Compression Based on Geoffery Hinton's Logit Regression Method in Keras applied to MNIST 16x compression over 0.95 percent accuracy.An Implementation of "Distilling the Knowledge in a Neural Network - Geoffery Hinton et. al"
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Bert Of Theseus⛵️The official PyTorch implementation for "BERT-of-Theseus: Compressing BERT by Progressive Module Replacing" (EMNLP 2020).
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Awesome Automl And Lightweight ModelsA list of high-quality (newest) AutoML works and lightweight models including 1.) Neural Architecture Search, 2.) Lightweight Structures, 3.) Model Compression, Quantization and Acceleration, 4.) Hyperparameter Optimization, 5.) Automated Feature Engineering.
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Auto-CompressionAutomatic DNN compression tool with various model compression and neural architecture search techniques
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NniAn open source AutoML toolkit for automate machine learning lifecycle, including feature engineering, neural architecture search, model compression and hyper-parameter tuning.
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Regularization-Pruning[ICLR'21] PyTorch code for our paper "Neural Pruning via Growing Regularization"
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Model OptimizationA toolkit to optimize ML models for deployment for Keras and TensorFlow, including quantization and pruning.
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Kd libA Pytorch Knowledge Distillation library for benchmarking and extending works in the domains of Knowledge Distillation, Pruning, and Quantization.
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Ld NetEfficient Contextualized Representation: Language Model Pruning for Sequence Labeling
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Ghostnet.pytorch[CVPR2020] GhostNet: More Features from Cheap Operations
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BitPackBitPack is a practical tool to efficiently save ultra-low precision/mixed-precision quantized models.
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Pretrained Language ModelPretrained language model and its related optimization techniques developed by Huawei Noah's Ark Lab.
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HawqQuantization library for PyTorch. Support low-precision and mixed-precision quantization, with hardware implementation through TVM.
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PocketflowAn Automatic Model Compression (AutoMC) framework for developing smaller and faster AI applications.
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Micronetmicronet, 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、regular and group convolutional channel pruning; 3、 group convolution structure; 4、batch-normalization fuse for quantization. deploy: tensorrt, fp32/fp16/int8(ptq-calibration)、op-adapt(upsample)、dynamic_shape
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SViTE[NeurIPS'21] "Chasing Sparsity in Vision Transformers: An End-to-End Exploration" by Tianlong Chen, Yu Cheng, Zhe Gan, Lu Yuan, Lei Zhang, Zhangyang Wang
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Awesome PruningA curated list of neural network pruning resources.
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JfasttextJava interface for fastText
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Channel PruningChannel Pruning for Accelerating Very Deep Neural Networks (ICCV'17)
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ATMC[NeurIPS'2019] Shupeng Gui, Haotao Wang, Haichuan Yang, Chen Yu, Zhangyang Wang, Ji Liu, “Model Compression with Adversarial Robustness: A Unified Optimization Framework”
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LightctrLightweight and Scalable framework that combines mainstream algorithms of Click-Through-Rate prediction based computational DAG, philosophy of Parameter Server and Ring-AllReduce collective communication.
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Amc Models[ECCV 2018] AMC: AutoML for Model Compression and Acceleration on Mobile Devices
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Yolov3yolov3 by pytorch
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CondensaProgrammable Neural Network Compression
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ZAQ-codeCVPR 2021 : Zero-shot Adversarial Quantization (ZAQ)
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MicroexpnetMicroExpNet: An Extremely Small and Fast Model For Expression Recognition From Frontal Face Images
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Soft Filter PruningSoft Filter Pruning for Accelerating Deep Convolutional Neural Networks
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Tf2An Open Source Deep Learning Inference Engine Based on FPGA
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DS-Net(CVPR 2021, Oral) Dynamic Slimmable Network
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GhostnetCV backbones including GhostNet, TinyNet and TNT, developed by Huawei Noah's Ark Lab.
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allie🤖 A machine learning framework for audio, text, image, video, or .CSV files (50+ featurizers and 15+ model trainers).
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NeuronblocksNLP DNN Toolkit - Building Your NLP DNN Models Like Playing Lego
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AquvitaeThe Easiest Knowledge Distillation Library for Lightweight Deep Learning
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Amc[ECCV 2018] AMC: AutoML for Model Compression and Acceleration on Mobile Devices
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CompressCompressing Representations for Self-Supervised Learning
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ESNACLearnable Embedding Space for Efficient Neural Architecture Compression
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Knowledge Distillation PytorchA PyTorch implementation for exploring deep and shallow knowledge distillation (KD) experiments with flexibility
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Mobile IdDeep Face Model Compression
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BipointnetThis project is the official implementation of our accepted ICLR 2021 paper BiPointNet: Binary Neural Network for Point Clouds.
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PaddleslimPaddleSlim is an open-source library for deep model compression and architecture search.
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Awesome Ml Model CompressionAwesome machine learning model compression research papers, tools, and learning material.
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FastPosepytorch realtime multi person keypoint estimation
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PruningCode for "Co-Evolutionary Compression for Unpaired Image Translation" (ICCV 2019) and "SCOP: Scientific Control for Reliable Neural Network Pruning" (NeurIPS 2020).
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Filter Pruning Geometric MedianFilter Pruning via Geometric Median for Deep Convolutional Neural Networks Acceleration (CVPR 2019 Oral)
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DLCV2018SPRINGDeep Learning for Computer Vision (CommE 5052) in NTU
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