Efficient-ML / Awesome-Model-Quantization
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.
☆2,093Updated 2 months ago
Alternatives and similar repositories for Awesome-Model-Quantization
Users that are interested in Awesome-Model-Quantization are comparing it to the libraries listed below
Sorting:
- A curated list of neural network pruning resources.☆2,440Updated last year
- List of papers related to neural network quantization in recent AI conferences and journals.☆618Updated last month
- Collection of recent methods on (deep) neural network compression and acceleration.☆947Updated last month
- Model Quantization Benchmark☆803Updated 3 weeks ago
- Awesome machine learning model compression research papers, quantization, tools, and learning material.☆517Updated 7 months ago
- Summary, Code for Deep Neural Network Quantization☆547Updated 7 months ago
- A simple network quantization demo using pytorch from scratch.☆530Updated last year
- Awesome LLM compression research papers and tools.☆1,502Updated last week
- [CVPR 2023] DepGraph: Towards Any Structural Pruning; LLMs, Vision Foundation Models, etc.☆3,000Updated 3 weeks ago
- PPL Quantization Tool (PPQ) is a powerful offline neural network quantization tool.☆1,687Updated last year
- Quantization library for PyTorch. Support low-precision and mixed-precision quantization, with hardware implementation through TVM.☆432Updated 2 years ago
- [ICML 2023] SmoothQuant: Accurate and Efficient Post-Training Quantization for Large Language Models☆1,401Updated 10 months ago
- micronet, a model compression and deploy lib. compression: 1、quantization: quantization-aware-training(QAT), High-Bit(>2b)(DoReFa/Quantiz…☆2,247Updated last week
- A curated list for Efficient Large Language Models☆1,651Updated 3 weeks ago
- [TMLR 2024] Efficient Large Language Models: A Survey☆1,151Updated last month
- A coding-free framework built on PyTorch for reproducible deep learning studies. PyTorch Ecosystem. 🏆25 knowledge distillation methods p…☆1,499Updated this week
- ☆245Updated 8 months ago
- ☆668Updated 3 years ago
- [ICLR 2020] Once for All: Train One Network and Specialize it for Efficient Deployment☆1,912Updated last year
- Rethinking the Value of Network Pruning (Pytorch) (ICLR 2019)☆1,514Updated 4 years ago
- Neural Network Distiller by Intel AI Lab: a Python package for neural network compression research. https://intellabs.github.io/distille…☆4,390Updated 2 years ago
- [ECCV 2018] AMC: AutoML for Model Compression and Acceleration on Mobile Devices☆441Updated last year
- Pytorch implementation of various Knowledge Distillation (KD) methods.☆1,690Updated 3 years ago
- PyTorch library to facilitate development and standardized evaluation of neural network pruning methods.☆429Updated last year
- PyTorch implementation for the APoT quantization (ICLR 2020)☆273Updated 5 months ago
- [IJCAI 2022] FQ-ViT: Post-Training Quantization for Fully Quantized Vision Transformer☆338Updated 2 years ago
- [CVPR 2019, Oral] HAQ: Hardware-Aware Automated Quantization with Mixed Precision☆384Updated 4 years ago
- AIMET is a library that provides advanced quantization and compression techniques for trained neural network models.☆2,302Updated this week
- Awasome Papers and Resources in Deep Neural Network Pruning with Source Code.☆159Updated 8 months ago
- Papers for deep neural network compression and acceleration☆397Updated 3 years ago