talenz

segment-anything-2

The repository provides code for running inference with the Meta Segment Anything Model 2 (SAM 2), links for downloading the trained model checkpoints, and example notebooks that show how to use the model.

llmc

This is the official PyTorch implementation of "LLMC: Benchmarking Large Language Model Quantization with a Versatile Compression Toolkit".

GroundingDINO

[ECCV 2024] Official implementation of the paper "Grounding DINO: Marrying DINO with Grounded Pre-Training for Open-Set Object Detection"

I-BERT

[ICML'21 Oral] I-BERT: Integer-only BERT Quantization

Awesome-Multimodal-Large-Language-Models

:sparkles::sparkles:Latest Advances on Multimodal Large Language Models

kinetics-downloader

Download DeepMind's Kinetics dataset.

MQBench

Model Quantization Benchmark

F8Net

[ICLR 2022 Oral] F8Net: Fixed-Point 8-bit Only Multiplication for Network Quantization

Nonuniform-to-Uniform-Quantization

Nonuniform-to-Uniform Quantization: Towards Accurate Quantization via Generalized Straight-Through Estimation. In CVPR 2022.

larq

An Open-Source Library for Training Binarized Neural Networks

ReCU

Pytorch implementation of our paper accepted by ICCV 2021 -- ReCU: Reviving the Dead Weights in Binary Neural Networks http://arxiv.org/abs/2103.12369

DAQ

An official PyTorch implementation of the paper "Distance-aware Quantization", ICCV 2021.

temporal-shift-module

[ICCV 2019] TSM: Temporal Shift Module for Efficient Video Understanding

BiDet

This is the official pytorch implementation for paper: BiDet: An Efficient Binarized Object Detector, which is accepted by CVPR2020.

PyHessian

PyHessian is a Pytorch library for second-order based analysis and training of Neural Networks

FracBits

Neural Network Quantization With Fractional Bit-widths

Double-Win-Quant

[ICML 2021] "Double-Win Quant: Aggressively Winning Robustness of Quantized DeepNeural Networks via Random Precision Training and Inference" by Yonggan Fu, Qixuan Yu, Meng Li, Vikas Chandra, Yingyan Lin

Yet-Another-EfficientDet-Pytorch

The pytorch re-implement of the official efficientdet with SOTA performance in real time and pretrained weights.

scale-adjusted-training

PyTorch implementation of Towards Efficient Training for Neural Network Quantization

permute-quantize-finetune

Using ideas from product quantization for state-of-the-art neural network compression.

EWGS

An official implementation of "Network Quantization with Element-wise Gradient Scaling" (CVPR 2021) in PyTorch.

leetcode_101

LeetCode 101：和你一起你轻松刷题（C++）

FAT_Quantization

Pytorch implementation for FAT: learning low-bitwidth parametric representation via frequency-aware transformation

PROFIT

ai-research-code

aimet

AIMET is a library that provides advanced quantization and compression techniques for trained neural network models.

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.

BRECQ

Pytorch implementation of BRECQ, ICLR 2021

BSQ

BSQ: Exploring Bit-Level Sparsity for Mixed-Precision Neural Network Quantization (ICLR 2021)

tinyml