PyTorch Quantization Aware Training Example
A nnie quantization aware training tool on pytorch.
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-Ari...
翻译 - 基于pytorch的模型压缩（1，量化：8/4 / 2bits（dorefa），三进制/二进制值（twn / bnn / xnornet）； 2，修剪：常规，常规和组卷积通道修剪； 3，组卷积结构； 4，特征（A）的二进制值的分批归一化折叠）
EfficientQAT: Efficient Quantization-Aware Training for Large Language Models
Quantization Aware Training
Code repo for the paper "LLM-QAT Data-Free Quantization Aware Training for Large Language Models"
Simulate quantization and quantization aware training for MXNet-Gluon models.
quantize aware training package for NCNN on pytorch
Quantization-aware training with spiking neural networks
tensorflow quantization aware training（利用TensorFlow实现模型伪量化）
[MLSys 2024 Best Paper Award] AWQ: Activation-aware Weight Quantization for LLM Compression and Acceleration
[CVPR 2019, Oral] HAQ: Hardware-Aware Automated Quantization with Mixed Precision
Post-training static quantization using ResNet18 architecture
[ICML 2023] SmoothQuant: Accurate and Efficient Post-Training Quantization for Large Language Models
[IJCAI 2022] FQ-ViT: Post-Training Quantization for Fully Quantized Vision Transformer
Code for the ICLR 2023 paper "GPTQ: Accurate Post-training Quantization of Generative Pretrained Transformers".
Neural Network Quantization & Low-Bit Fixed Point Training For Hardware-Friendly Algorithm Design
Training and Testing codes for our paper "Real-world Image Super-resolution via Domain-distance Aware Training"
About Explicit Variance Minimization: Training Neural Networks for Medical Imaging With Limited Data Annotations
color quantization lib
EasyQuant(EQ) is an efficient and simple post-training quantization method via effectively optimizing the scales of weights and activations.
翻译 - EasyQuant（EQ）是一种有效且简单的训练后量化方法，它可以有效地优化权重和激活的比例。