There are 7 repositories under quantized-neural-networks topic.
A toolkit to optimize ML models for deployment for Keras and TensorFlow, including quantization and pruning.
The Hailo Model Zoo includes pre-trained models and a full building and evaluation environment
Generate a quantization parameter file for ncnn framework int8 inference
Quantization library for PyTorch. Support low-precision and mixed-precision quantization, with hardware implementation through TVM.
[CVPR'20] ZeroQ: A Novel Zero Shot Quantization Framework
QONNX: Arbitrary-Precision Quantized Neural Networks in ONNX
Mobilenet v1 trained on Imagenet for STM32 using extended CMSIS-NN with INT-Q quantization support
Some recent Quantizing techniques on PyTorch
Slides with modifications for a course at Tsinghua University.
BitPack is a practical tool to efficiently save ultra-low precision/mixed-precision quantized models.
[NeurIPS 2023 Spotlight] This project is the official implementation of our accepted NeurIPS 2023 (spotlight) paper QuantSR: Accurate Low-bit Quantization for Efficient Image Super-Resolution.
This repository containts the pytorch scripts to train mixed-precision networks for microcontroller deployment, based on the memory contraints of the target device.
This repository contains source code to binarize any real-value word embeddings into binary vectors.
Low Precision(quantized) Yolov5
Training wide residual networks for deployment using a single bit for each weight - Official Code Repository for ICLR 2018 Published Paper
Binary neural networks developed by Huawei Noah's Ark Lab
Contains code for Binary, Ternary, N-bit Quantized and Hybrid CNNs for low precision experiments.
An Efficient Matrix Multiplication Algorithm for Accelerating Inference in Binary and Ternary Neural Networks
Mobilint Model Zoo Project
Code implementation of our AISTATS'21 paper "Mirror Descent View for Neural Network Quantization"
Efficient Neural Architecture Search coupled with Quantized CNNs to search for resource efficient and accurate architectures.
Modeling stuck-at faults for RRAM inference on popular neural networks after quantization
Mobilenet v1 (3,160,160, alpha=0.25, and 3,192,192, alpha=0.5) on STM32H7 using X-CUBE-AI v4.1.0
DCASE 2020 Challenge Task 1B - Low-Complexity Acoustic Scene Classification
Code implementation of our AAAI'22 paper "Improved Gradient-Based Adversarial Attacks for Quantized Networks"
Quantized training using Keras
In this project, we have implemented the VQ-VAE algorithm on both MNIST and CIFAR10 datasets considering MSELOSS and also NLLLOSE.
Autonomous Driving project for exploration of robotic perception, sensor fusion and autonomous navigation.
Curated list of Deep Neural Networks on FPGAs research papers
A python-based utility to convert a grayscale image into verilog code.