Topic: post-training-quantization Goto Github
Some thing interesting about post-training-quantization
Some thing interesting about post-training-quantization
post-training-quantization,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
User: 666dzy666
post-training-quantization,TinyNeuralNetwork is an efficient and easy-to-use deep learning model compression framework.
Organization: alibaba
post-training-quantization,Research experiments archive for post-training quantization with TensorRT. Submitted and Accepted to IEEE EDGE 2024
Organization: amikom-gace-research-group
post-training-quantization,A framework to train a ResUNet architecture, quantize, compile and execute it on an FPGA.
User: andrea-zanette
post-training-quantization,Low-bit (2/4/8/16) Post Training Quantization for ResNet20
User: andreizoltan
post-training-quantization,The repository discusses a research work published on MDPI Sensors and provides details about the project.
User: generalmg
post-training-quantization,[CAAI AIR'24] Minimize Quantization Output Error with Bias Compensation
User: gongcheng1919
post-training-quantization,Notes on quantization in neural networks
User: hkproj
Home Page: https://www.youtube.com/watch?v=0VdNflU08yA
post-training-quantization,SOTA low-bit LLM quantization (INT8/FP8/INT4/FP4/NF4) & sparsity; leading model compression techniques on TensorFlow, PyTorch, and ONNX Runtime
Organization: intel
Home Page: https://intel.github.io/neural-compressor/
post-training-quantization,Improved the performance of 8-bit PTQ4DM expecially on FID.
User: iszry
post-training-quantization,
User: kwanghoonan
post-training-quantization,This sample shows how to convert TensorFlow model to OpenVINO IR model and how to quantize OpenVINO model.
User: likholat
post-training-quantization,[IJCAI 2022] FQ-ViT: Post-Training Quantization for Fully Quantized Vision Transformer
Organization: megvii-research
post-training-quantization,A model compression and acceleration toolbox based on pytorch.
Organization: megvii-research
post-training-quantization,This is the official PyTorch implementation of "LLMC: Benchmarking Large Language Model Quantization with a Versatile Compression Toolkit".
Organization: modeltc
Home Page: https://arxiv.org/abs/2405.06001
post-training-quantization,[ICLR 2024] This is the official PyTorch implementation of "QLLM: Accurate and Efficient Low-Bitwidth Quantization for Large Language Models"
Organization: modeltc
Home Page: https://arxiv.org/abs/2310.08041
post-training-quantization,[CVPR 2024 Highlight] This is the official PyTorch implementation of "TFMQ-DM: Temporal Feature Maintenance Quantization for Diffusion Models".
Organization: modeltc
Home Page: https://modeltc.github.io/TFMQ-DM/
post-training-quantization,EfficientNetV2 (Efficientnetv2-b2) and quantization int8 and fp32 (QAT and PTQ) on CK+ dataset . fine-tuning, augmentation, solving imbalanced dataset, etc.
User: omidghadami95
post-training-quantization,Post-Training quantization perfomed on the model trained with CLIC dataset.
User: raj2022
post-training-quantization,Creating Snapdragon neural processing engine environment to convert protobuf(pb) files to dlc(deep learning container) files as well as use snpe for Quantizing neural networks. Mobile app development link https://github.com/anshumax/mobilenn
User: rioter1
post-training-quantization,Post-training quantization on Nvidia Nemo ASR model
User: rumeysakeskin
post-training-quantization,Post-training static quantization using ResNet18 architecture
User: sanjana7395
post-training-quantization,Model Quantization with Pytorch, Tensorflow & Larq
User: satya15july
post-training-quantization,This repository contains notebooks that show the usage of TensorFlow Lite for quantizing deep neural networks.
User: sayakpaul
post-training-quantization,Post post-training-quantization (PTQ) method for improving LLMs. Unofficial implementation of https://arxiv.org/abs/2309.02784
User: smpanaro
post-training-quantization,[ICML 2024] SqueezeLLM: Dense-and-Sparse Quantization
Organization: squeezeailab
Home Page: https://arxiv.org/abs/2306.07629
post-training-quantization,Implementation of EPTQ - an Enhanced Post-Training Quantization algorithm for DNN compression
Organization: ssi-research
post-training-quantization,Quantization for Object Detection in Tensorflow 2.x
User: tanyachutani
post-training-quantization,[ICCV 2023] Q-Diffusion: Quantizing Diffusion Models.
User: xiuyu-li
Home Page: https://xiuyuli.com/qdiffusion/
post-training-quantization,Comprehensive study on the quantization of various CNN models, employing techniques such as Post-Training Quantization and Quantization Aware Training (QAT).
User: yashmaniya0
post-training-quantization,quantization example for pqt & qat
User: yester31
post-training-quantization,Generating tensorrt model using onnx
User: yester31
post-training-quantization,Pytorch implementation of our paper accepted by ECCV 2022-- Fine-grained Data Distribution Alignment for Post-Training Quantization
User: zysxmu
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