quantization-aware-training
There are 58 repositories under quantization-aware-training topic.
666DZY666/micronet
micronet, a model compression and deploy lib. compression: 1、quantization: quantization-aware-training(QAT), High-Bit(>2b)(DoReFa/Quantization and Training of Neural Networks for Efficient Integer-Arithmetic-Only Inference)、Low-Bit(≤2b)/Ternary and Binary(TWN/BNN/XNOR-Net); post-training-quantization(PTQ), 8-bit(tensorrt); 2、 pruning: normal、regular and group convolutional channel pruning; 3、 group convolution structure; 4、batch-normalization fuse for quantization. deploy: tensorrt, fp32/fp16/int8(ptq-calibration)、op-adapt(upsample)、dynamic_shape
intel/neural-compressor
SOTA low-bit LLM quantization (INT8/FP8/INT4/FP4/NF4) & sparsity; leading model compression techniques on TensorFlow, PyTorch, and ONNX Runtime
openvinotoolkit/nncf
Neural Network Compression Framework for enhanced OpenVINO™ inference
alibaba/TinyNeuralNetwork
TinyNeuralNetwork is an efficient and easy-to-use deep learning model compression framework.
SpursLipu/YOLOv3v4-ModelCompression-MultidatasetTraining-Multibackbone
YOLO ModelCompression MultidatasetTraining
megvii-research/Sparsebit
A model compression and acceleration toolbox based on pytorch.
fastmachinelearning/hls4ml-tutorial
Tutorial notebooks for hls4ml
Beomi/BitNet-Transformers
0️⃣1️⃣🤗 BitNet-Transformers: Huggingface Transformers Implementation of "BitNet: Scaling 1-bit Transformers for Large Language Models" in pytorch with Llama(2) Architecture
THU-MIG/torch-model-compression
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
sayakpaul/Adventures-in-TensorFlow-Lite
This repository contains notebooks that show the usage of TensorFlow Lite for quantizing deep neural networks.
clovaai/frostnet
FrostNet: Towards Quantization-Aware Network Architecture Search
openvinotoolkit/mmdetection
OpenVINO Training Extensions Object Detection
jahongir7174/YOLOv8-qat
Quantization Aware Training
mlzxy/qsparse
Train neural networks with joint quantization and pruning on both weights and activations using any pytorch modules
hkproj/quantization-notes
Notes on quantization in neural networks
yashbhalgat/QualcommAI-MicroNet-submission-MixNet
3rd place solution for NeurIPS 2019 MicroNet challenge
DeadAt0m/LSQFakeQuantize-PyTorch
FakeQuantize with Learned Step Size(LSQ+) as Observer in PyTorch
jeshraghian/QSNNs
Quantization-aware training with spiking neural networks
bharathsudharsan/CNN_on_MCU
Code for paper 'Multi-Component Optimization and Efficient Deployment of Neural-Networks on Resource-Constrained IoT Hardware'
HaoranREN/TensorFlow_Model_Quantization
A tutorial of model quantization using TensorFlow
Intelligent-Microsystems-Lab/SNNQuantPrune
Code for the ISCAS23 paper "The Hardware Impact of Quantization and Pruning for Weights in Spiking Neural Networks"
rishivar/Resnet-18
Image classification done with Mindspore technology
HanByulKim/BASQ
BASQ: Branch-wise Activation-clipping Search Quantization for Sub-4-bit Neural Networks, ECCV 2022
LorenzoValente3/Autoencoder-for-FPGA
Autoencoder model for FPGA implementation using hls4ml. Repository for Applied Electronics Project.
SangbumChoi/PyTorch_Quantization
all methods of pytorch quantization based on resnet50
yashbhalgat/QualcommAI-MicroNet-submission-EfficientNet
Submission name: QualcommAI-EfficientNet. MicroNet Challenge (NeurIPS 2019) submission - Qualcomm AI Research
yester31/Quantization_EX
quantization example for pqt & qat
etetteh/OoD_Gen-Chest_Xray
Multi-Domain Balanced Sampling Improves Out-of-Distribution Generalization of Chest X-ray Pathology Prediction Models
LorenzoValente3/JointVAE4AD
Disentangle joint continous and discrete representations for Anomaly Detection in High Energy Physics.
marekninja/master-thesis
One Bit at a Time: Impact of Quantisation on Neural Machine Translation
satya15july/quantization
Model Quantization with Pytorch, Tensorflow & Larq
yashmaniya0/Quantization-of-Image-Classification-Models
Comprehensive study on the quantization of various CNN models, employing techniques such as Post-Training Quantization and Quantization Aware Training (QAT).
moshiurtonmoy/A-Lightweight-Visual-Font-Style-Recognition-with-Quantized-Convolutional-Autoencoder
A lightweight Convolutional Autoencoder for recognizing Bangla font styles along with quantization for deploying resource-constrained IoT devices.
yihong1120/YOLOv8-qat
Quantization Aware Training