Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Making models smaller and faster: quantization, distillation, pruning, sparsity and kernel-level work.
Signals: quantization, model-compression, pruning, knowledge-distillation, gptq, awq, bitsandbytes, sparsity
184 results
利用pytorch实现图像分类的一个完整的代码，训练，预测，TTA，模型融合，模型部署，cnn提取特征，svm或者随机森林等进行分类，模型蒸馏，一个完整的代码
Dataflow compiler for QNN inference on FPGAs
FP16xINT4 LLM inference kernel that can achieve near-ideal ~4x speedups up to medium batchsizes of 16-32 tokens.
Z80-μLM is a 2-bit quantized language model small enough to run on an 8-bit Z80 processor. Train conversational models in Python, export them as CP/M .COM binaries, and chat with your vintage computer.
Efficient computing methods developed by Huawei Noah's Ark Lab
OpenMMLab Model Compression Toolbox and Benchmark.
A list of papers, docs, codes about model quantization. This repo is aimed to provide the info for model quantization research, we are continuously improving the project. Welcome to PR the works (papers, repositories) that are missed by the repo.
Base pretrained models and datasets in pytorch (MNIST, SVHN, CIFAR10, CIFAR100, STL10, AlexNet, VGG16, VGG19, ResNet, Inception, SqueezeNet)
Pretrained language model and its related optimization techniques developed by Huawei Noah's Ark Lab.
Lossy PNG compressor — pngquant command based on libimagequant library
Must-read papers on deep learning to hash (DeepHash)
An Open-Source Package for Deep Learning to Hash (DeepHash)
Always sparse. Never dense. But never say never. A Sparse Training repository for the Adaptive Sparse Connectivity concept and its algorithmic instantiation, i.e. Sparse Evolutionary Training, to boost Deep Learning scalability on various aspects (e.g. memory and computational time efficiency, representation and generalization power).
FasterAI: Prune and Distill your models with FastAI and PyTorch
Sparse Optimisation Research Code
Reference ImageNet implementation of SelecSLS CNN architecture proposed in the SIGGRAPH 2020 paper "XNect: Real-time Multi-Person 3D Motion Capture with a Single RGB Camera". The repository also includes code for pruning the model based on implicit sparsity emerging from adaptive gradient descent methods, as detailed in the CVPR 2019 paper "On implicit filter level sparsity in Convolutional Neural Networks".
Caffe for Sparse and Low-rank Deep Neural Networks
[NeurIPS'23] H2O: Heavy-Hitter Oracle for Efficient Generative Inference of Large Language Models.
[ICCV 2023] Q-Diffusion: Quantizing Diffusion Models.
Knowledge distillation methods implemented with Tensorflow (now there are 11 (+1) methods, and will be added more.)
A 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.
针对pytorch模型的自动化模型结构分析和修改工具集，包含自动分析模型结构的模型压缩算法库
A model compression and acceleration toolbox based on pytorch.
More readable and flexible yolov5 with more backbone(gcn, resnet, shufflenet, moblienet, efficientnet, hrnet, swin-transformer, etc) and (cbam，dcn and so on), and tensorrt
24,523 repositories in the index in total.
