#Pruning
Showing 37 of 37 repositories tagged #pruning, ranked by stars
《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
[CVPR 2023] DepGraph: Towards Any Structural Pruning; LLMs, Vision Foundation Models, etc.
Sparsity-aware deep learning inference runtime for CPUs
AIMET is a library that provides advanced quantization and compression techniques for trained neural network models.
Config driven, easy backup cli for restic.
A toolkit to optimize ML models for deployment for Keras and TensorFlow, including quantization and pruning.
Neural Network Compression Framework for enhanced OpenVINO™ inference
[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.
PyTorch Implementation of [1611.06440] Pruning Convolutional Neural Networks for Resource Efficient Inference
TinyNeuralNetwork is an efficient and easy-to-use deep learning model compression framework.
Embedded and mobile deep learning research resources
[EMNLP 2024 & AAAI 2026] A powerful toolkit for compressing large models including LLMs, VLMs, and video generative models.
A Pytorch Knowledge Distillation library for benchmarking and extending works in the domains of Knowledge Distillation, Pruning, and Quantization.
[ICLR 2024] Sheared LLaMA: Accelerating Language Model Pre-training via Structured Pruning
Awesome machine learning model compression research papers, quantization, tools, and learning material.
Infrastructures™ for Machine Learning Training/Inference in Production.
大模型/LLM推理和部署理论与实践
Neural network model repository for highly sparse and sparse-quantized models with matching sparsification recipes
Context cleaning for Claude Code — prune bloated sessions, protect Agent Teams from context loss, auto-guard with tiered pruning
ML model optimization product to accelerate inference.
(CVPR 2025) Adversarial Diffusion Compression for Real-World Image Super-Resolution [PyTorch]
FasterAI: Prune and Distill your models with FastAI and PyTorch
Observations and notes to understand the workings of neural network models and other thought experiments using Tensorflow
Repository to track the progress in model compression and acceleration
Prune DNN using Alternating Direction Method of Multipliers (ADMM)
ArgoCD-Basics-to-Production is a beginner-friendly repository designed to help you understand GitOps and Argo CD from fundamentals to real-world production use. It covers GitOps concepts, Argo CD architecture, and hands-on deployment workflows, organized as a progressive learning series.
Can We Find Strong Lottery Tickets in Generative Models? - Official Code (Pytorch)
[CVPR 2025] DivPrune: Diversity-based Visual Token Pruning for Large Multimodal Models
PyTorch model training and layer saturation monitor
Official Pytorch Implementation of "Outlier Weighed Layerwise Sparsity (OWL): A Missing Secret Sauce for Pruning LLMs to High Sparsity"
I demonstrate how to compress a neural network using pruning in tensorflow.
[AAAI 2024] Fluctuation-based Adaptive Structured Pruning for Large Language Models
Deep learning research implemented on notebooks using PyTorch.
Train neural networks with joint quantization and pruning on both weights and activations using any pytorch modules
Hyperspectral CNN compression and band selection
A walkthrough of how to prune keras models, using both weight-pruning and unit/neuron-pruning.
the GHOST protocol implementation on solidity.