Pytorch Model Quantization

Model Zoo - generative-models PyTorch Model

Model Zoo - generative-models PyTorch Model

Deep Compression: Optimization Techniques for Inference & Efficiency

Deep Compression: Optimization Techniques for Inference & Efficiency

Code Trace of ML-KSW-for-MCU and Speech_commands | allenlu2007

Code Trace of ML-KSW-for-MCU and Speech_commands | allenlu2007

Keras - Save and Load Your Deep Learning Models - PyImageSearch

Keras - Save and Load Your Deep Learning Models - PyImageSearch

Data-Free Quantization through Weight Equalization and Bias

Data-Free Quantization through Weight Equalization and Bias

How to run Keras model on RK3399Pro | DLology

How to run Keras model on RK3399Pro | DLology

Glow: Graph Lowering Compiler Techniques for Neural Networks – arXiv

Glow: Graph Lowering Compiler Techniques for Neural Networks – arXiv

An Empirical Study of Pruning and Quantization Methods for Neural

An Empirical Study of Pruning and Quantization Methods for Neural

Distiller: Distiller 是 Intel 开源的一个用于神经网络压缩的 Python 包

Distiller: Distiller 是 Intel 开源的一个用于神经网络压缩的 Python 包

QNNPACK: Open source library for optimized mobile deep learning

QNNPACK: Open source library for optimized mobile deep learning

Introduction to PyTorch Model Compression Through Teacher-Student

Introduction to PyTorch Model Compression Through Teacher-Student

GitHub - mit-han-lab/haq-release: [CVPR 2019, Oral] HAQ: Hardware

GitHub - mit-han-lab/haq-release: [CVPR 2019, Oral] HAQ: Hardware

Compression and Acceleration of High-dimensional Neural Networks

Compression and Acceleration of High-dimensional Neural Networks

Realtime ML + Kubernetes + TensorFlow + KubeFlow + MLflow +

Realtime ML + Kubernetes + TensorFlow + KubeFlow + MLflow +

Profillic: AI research & source code to supercharge your projects

Profillic: AI research & source code to supercharge your projects

A thread written by @programmer:

A thread written by @programmer: "🔧 Its a long weekend, I only

Learning to Quantize Deep Networks by Optimizing Quantization

Learning to Quantize Deep Networks by Optimizing Quantization

Joint Neural Architecture Search and Quantization

Joint Neural Architecture Search and Quantization

TensorRT Developer Guide :: Deep Learning SDK Documentation

TensorRT Developer Guide :: Deep Learning SDK Documentation

Sensors | Free Full-Text | Mapping Neural Networks to FPGA-Based IoT

Sensors | Free Full-Text | Mapping Neural Networks to FPGA-Based IoT

Lower Numerical Precision Deep Learning Inference and Training

Lower Numerical Precision Deep Learning Inference and Training

DLRM: An advanced, open source deep learning recommendation model

DLRM: An advanced, open source deep learning recommendation model

Quantizing Deep Convolutional Networks for Efficient Inference

Quantizing Deep Convolutional Networks for Efficient Inference

Contrast to reproduce 34 pre-training models, who do you choose for

Contrast to reproduce 34 pre-training models, who do you choose for

Quoc Le on Twitter:

Quoc Le on Twitter: "Introducing MobileNetV3: Based on MNASNet

Can't convert mobilenet v2 quantized model from tensorflow to Onnx

Can't convert mobilenet v2 quantized model from tensorflow to Onnx

How to run deep learning model on microcontroller with CMSIS-NN

How to run deep learning model on microcontroller with CMSIS-NN

InsideNet: A tool for characterizing convolutional neural networks

InsideNet: A tool for characterizing convolutional neural networks

TensorFlow for Poets 2: TFLite Android

TensorFlow for Poets 2: TFLite Android

Papers With Code : Efficient Neural Architecture Search via

Papers With Code : Efficient Neural Architecture Search via

Model Quantization for PyTorch (Proposal) · Issue #18318 · pytorch

Model Quantization for PyTorch (Proposal) · Issue #18318 · pytorch

Machine Learning on Mobile - Source Diving

Machine Learning on Mobile - Source Diving

MXNet Operator Benchmarks - MXNet - Apache Software Foundation

MXNet Operator Benchmarks - MXNet - Apache Software Foundation

Sensors | Free Full-Text | FPGA-Based Hybrid-Type Implementation of

Sensors | Free Full-Text | FPGA-Based Hybrid-Type Implementation of

Contrast to reproduce 34 pre-training models, who do you choose for

Contrast to reproduce 34 pre-training models, who do you choose for

pytorch data type is

pytorch data type is "NCHW" but tensorflow data type is "NHWC", when

Sensors | Free Full-Text | Mapping Neural Networks to FPGA-Based IoT

Sensors | Free Full-Text | Mapping Neural Networks to FPGA-Based IoT

Google Releases TensorFlow 1 7 0! All You Need to Know

Google Releases TensorFlow 1 7 0! All You Need to Know

Federated Learning: Rewards & Challenges of Distributed Private ML

Federated Learning: Rewards & Challenges of Distributed Private ML

The future of AI is in mobile & IoT devices(Part I)

The future of AI is in mobile & IoT devices(Part I)

Table 2 from NICE: Noise Injection and Clamping Estimation for

Table 2 from NICE: Noise Injection and Clamping Estimation for

Bit-width Comparison of Activation Quantization  | Download Table

Bit-width Comparison of Activation Quantization | Download Table

Use TensorRT to speed up neural network (read ONNX model and run

Use TensorRT to speed up neural network (read ONNX model and run

Chapter 1 - Introduction to adversarial robustness

Chapter 1 - Introduction to adversarial robustness

Applied Sciences | Free Full-Text | Efficient Weights Quantization

Applied Sciences | Free Full-Text | Efficient Weights Quantization

Value-aware Quantization for Training and Inference of Neural Networks

Value-aware Quantization for Training and Inference of Neural Networks

Habana, the AI chip innovator, promises top performance and

Habana, the AI chip innovator, promises top performance and

How to perform quantization of a model in PyTorch? - glow - PyTorch

How to perform quantization of a model in PyTorch? - glow - PyTorch

PDF] QGAN: Quantized Generative Adversarial Networks - Semantic Scholar

PDF] QGAN: Quantized Generative Adversarial Networks - Semantic Scholar

ADA-Tucker: Compressing deep neural networks via adaptive dimension

ADA-Tucker: Compressing deep neural networks via adaptive dimension

Everything you need to know about TensorFlow 2 0 - By Thalles Silva

Everything you need to know about TensorFlow 2 0 - By Thalles Silva

Bit-width Comparison of Activation Quantization  | Download Table

Bit-width Comparison of Activation Quantization | Download Table

transformers zip: Compressing Transformers with Pruning and Quantization

transformers zip: Compressing Transformers with Pruning and Quantization

Compressing Neural Networks with Intel AI Lab's Distiller

Compressing Neural Networks with Intel AI Lab's Distiller

Deep learning on mobile devices: a review

Deep learning on mobile devices: a review

R Shiny for Rapid Prototyping of Data Products

R Shiny for Rapid Prototyping of Data Products

Reducing the size of a Core ML model: a deep dive into quantization

Reducing the size of a Core ML model: a deep dive into quantization

arXiv:1905 12253v1 [cs LG] 29 May 2019

arXiv:1905 12253v1 [cs LG] 29 May 2019

Improving Neural Network Quantization without Retraining using

Improving Neural Network Quantization without Retraining using

MXNet nGraph integration using subgraph backend interface - MXNet

MXNet nGraph integration using subgraph backend interface - MXNet

Introduction to Embedding in Natural Language Processing

Introduction to Embedding in Natural Language Processing

arXiv:1906 04721v1 [cs LG] 11 Jun 2019

arXiv:1906 04721v1 [cs LG] 11 Jun 2019

Use Automatic Mixed Precision on Tensor Cores in Frameworks Today

Use Automatic Mixed Precision on Tensor Cores in Frameworks Today

Low-Memory Neural Network Training: A Technical Report – arXiv Vanity

Low-Memory Neural Network Training: A Technical Report – arXiv Vanity

QNNPACK: Open source library for optimized mobile deep learning

QNNPACK: Open source library for optimized mobile deep learning

PyTorch 1 0: Facebook's Very Own AI Framework Built On Python

PyTorch 1 0: Facebook's Very Own AI Framework Built On Python

DISCOVERING LOW-PRECISION NETWORKS CLOSE TO FULL-PRECISION NETWORKS

DISCOVERING LOW-PRECISION NETWORKS CLOSE TO FULL-PRECISION NETWORKS

Why INT4 is presented as performance of GPUs? - Deep Learning - Deep

Why INT4 is presented as performance of GPUs? - Deep Learning - Deep

Model Zoo - generative-models PyTorch Model

Model Zoo - generative-models PyTorch Model

Distiller: Distiller 是 Intel 开源的一个用于神经网络压缩的 Python 包

Distiller: Distiller 是 Intel 开源的一个用于神经网络压缩的 Python 包

Euplotid: A quantized geometric model of the eukaryotic cell | bioRxiv

Euplotid: A quantized geometric model of the eukaryotic cell | bioRxiv

TensorRT Developer Guide :: Deep Learning SDK Documentation

TensorRT Developer Guide :: Deep Learning SDK Documentation

Post-training quantization | TensorFlow Lite | TensorFlow

Post-training quantization | TensorFlow Lite | TensorFlow

Data-Free Quantization through Weight Equalization and Bias

Data-Free Quantization through Weight Equalization and Bias

arXiv:1812 08301v1 [cs CV] 20 Dec 2018

arXiv:1812 08301v1 [cs CV] 20 Dec 2018

Value-aware Quantization for Training and Inference of Neural Networks

Value-aware Quantization for Training and Inference of Neural Networks

Introduction to PyTorch Model Compression Through Teacher-Student

Introduction to PyTorch Model Compression Through Teacher-Student

P] Model Pruning and Quantization in Tensorflow : MachineLearning

P] Model Pruning and Quantization in Tensorflow : MachineLearning

Computation-Performance Optimization of Convolutional Neural

Computation-Performance Optimization of Convolutional Neural

Lower Numerical Precision Deep Learning Inference and Training

Lower Numerical Precision Deep Learning Inference and Training

In training quantization of weights (parameters) and activations

In training quantization of weights (parameters) and activations