Alternatives and similar repositories for OMPQ:

Users that are interested in OMPQ are comparing it to the libraries listed below

• lliai / EMQ-series
  [ICCV-2023] EMQ: Evolving Training-free Proxies for Automated Mixed Precision Quantization
  ☆25Updated last year
• ZiweiWangTHU / GMPQ
  This is the pytorch implementation for the paper: Generalizable Mixed-Precision Quantization via Attribution Rank Preservation, which is…
  ☆25Updated 3 years ago
• gilshm / sparq
  Post-training sparsity-aware quantization
  ☆34Updated last year
• 1hunters / LIMPQ
  Official implementation for paper LIMPQ, "Mixed-Precision Neural Network Quantization via Learned Layer-wise Importance", ECCV 2022
  ☆51Updated last year
• yukang2017 / NAS-quantization
  The code for Joint Neural Architecture Search and Quantization
  ☆13Updated 5 years ago
• z-hXu / ReCU
  Pytorch implementation of our paper accepted by ICCV 2021 -- ReCU: Reviving the Dead Weights in Binary Neural Networks http://arxiv.org/a…
  ☆39Updated 3 years ago
• HuangOwen / QAT-ACS
  [TMLR] Official PyTorch implementation of paper "Efficient Quantization-aware Training with Adaptive Coreset Selection"
  ☆30Updated 6 months ago
• MingSun-Tse / TPP
  [ICLR'23] Trainability Preserving Neural Pruning (PyTorch)
  ☆32Updated last year
• papers-submission / structured_transposable_masks
  Code for ICML 2021 submission
  ☆35Updated 3 years ago
• jakc4103 / scale-adjusted-training
  PyTorch implementation of Towards Efficient Training for Neural Network Quantization
  ☆15Updated 5 years ago
• WeixiangXu / STTN
  ☆17Updated 2 years ago
• zhaohui-yang / Binary-Neural-Networks
  Binary neural networks developed by Huawei Noah's Ark Lab
  ☆29Updated 4 years ago
• VITA-Group / BNN_NoBN
  [CVPRW 21] "BNN - BN = ? Training Binary Neural Networks without Batch Normalization", Tianlong Chen, Zhenyu Zhang, Xu Ouyang, Zechun Liu…
  ☆57Updated 3 years ago
• peiswang / BitSplit
  BitSplit Post-trining Quantization
  ☆48Updated 3 years ago
• chenbong / PSS-Net
  ☆16Updated 2 years ago
• MAC-AutoML / ITPruner
  ☆23Updated 3 years ago
• yuchaoli / CC
  Towards Compact CNNs via Collaborative Compression
  ☆11Updated 2 years ago
• GATECH-EIC / ShiftAddNet
  [NeurIPS 2020] ShiftAddNet: A Hardware-Inspired Deep Network
  ☆71Updated 4 years ago
• yaozhewei / HAP
  ☆43Updated last year
• Qualcomm-AI-research / oscillations-qat
  ☆75Updated 2 years ago
• deJQK / AdaBits
  ☆38Updated 2 years ago
• zysxmu / FDDA
  Pytorch implementation of our paper accepted by ECCV 2022-- Fine-grained Data Distribution Alignment for Post-Training Quantization
  ☆14Updated 2 years ago
• VITA-Group / Random_Pruning
  [ICLR 2022] The Unreasonable Effectiveness of Random Pruning: Return of the Most Naive Baseline for Sparse Training by Shiwei Liu, Tianlo…
  ☆73Updated 2 years ago
• HuangOwen / Quantization-Variation
  [TMLR] Official PyTorch implementation of paper "Quantization Variation: A New Perspective on Training Transformers with Low-Bit Precisio…
  ☆41Updated 4 months ago
• Yanqi-Chen / LATS
  To appear in the 11th International Conference on Learning Representations (ICLR 2023).
  ☆16Updated last year
• yanghr / BSQ
  BSQ: Exploring Bit-Level Sparsity for Mixed-Precision Neural Network Quantization (ICLR 2021)
  ☆38Updated 4 years ago
• sony-si / ai-research
  ☆47Updated 4 years ago
• IST-DASLab / spdy
  Code for ICML 2022 paper "SPDY: Accurate Pruning with Speedup Guarantees"
  ☆18Updated last year
• GATECH-EIC / CPT
  [ICLR 2021 Spotlight] "CPT: Efficient Deep Neural Network Training via Cyclic Precision" by Yonggan Fu, Han Guo, Meng Li, Xin Yang, Yinin…
  ☆30Updated 11 months ago
• GATECH-EIC / ShiftAddViT
  [NeurIPS 2023] ShiftAddViT: Mixture of Multiplication Primitives Towards Efficient Vision Transformer
  ☆32Updated last year