Alternatives and similar repositories for SQAKD

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

• htqin / BiBench
  [ICML 2023] This project is the official implementation of our accepted ICML 2023 paper BiBench: Benchmarking and Analyzing Network Binar…
  ☆56Updated last year
• HuangOwen / Quantization-Variation
  [TMLR] Official PyTorch implementation of paper "Quantization Variation: A New Perspective on Training Transformers with Low-Bit Precisio…
  ☆46Updated 8 months ago
• VITA-Group / Structure-LTH
  [ICML 2022] "Coarsening the Granularity: Towards Structurally Sparse Lottery Tickets" by Tianlong Chen, Xuxi Chen, Xiaolong Ma, Yanzhi Wa…
  ☆33Updated 2 years ago
• Qualcomm-AI-research / oscillations-qat
  ☆76Updated 2 years ago
• MingSun-Tse / Why-the-State-of-Pruning-so-Confusing
  [Preprint] Why is the State of Neural Network Pruning so Confusing? On the Fairness, Comparison Setup, and Trainability in Network Prunin…
  ☆40Updated 2 years ago
• HuangOwen / QAT-ACS
  [TMLR] Official PyTorch implementation of paper "Efficient Quantization-aware Training with Adaptive Coreset Selection"
  ☆32Updated 9 months ago
• Phuoc-Hoan-Le / BinaryViT
  BinaryViT: Pushing Binary Vision Transformers Towards Convolutional Models
  ☆36Updated last year
• Qualcomm-AI-research / pruning-vs-quantization
  ☆22Updated last year
• Ruichen0424 / AB-BNN
  [CVPR 2024] Offical implementation for A&B BNN: Add&Bit-Operation-Only Hardware-Friendly Binary Neural Network
  ☆25Updated 5 months ago
• Intelligent-Computing-Lab-Yale / TesseraQ
  ☆21Updated 7 months ago
• SteveTsui / ReBNN
  ☆12Updated last year
• NVlabs / NViT
  ☆21Updated last year
• htqin / DSG
  This project is the official implementation of our accepted IEEE TPAMI paper Diverse Sample Generation: Pushing the Limit of Data-free Qu…
  ☆14Updated 2 years ago
• MambaQuant / MambaQuant
  ☆20Updated last week
• gilshm / sparq
  Post-training sparsity-aware quantization
  ☆34Updated 2 years ago
• nbasyl / OFQ
  The official implementation of the ICML 2023 paper OFQ-ViT
  ☆30Updated last year
• vineeths96 / Compressed-Transformers
  In this repository, we explore model compression for transformer architectures via quantization. We specifically explore quantization awa…
  ☆24Updated 4 years ago
• ModelTC / Outlier_Suppression_Plus
  Official implementation of the EMNLP23 paper: Outlier Suppression+: Accurate quantization of large language models by equivalent and opti…
  ☆46Updated last year
• 1157942086 / CVPR2020_Auxiliary_Quantization
  Training Quantized Neural Networks with a Full-precision Auxiliary Module
  ☆13Updated 4 years ago
• huqinghao / PalQuant
  ☆12Updated 2 years ago
• hikvision-research / SAViT
  ☆12Updated last year
• lliai / EMQ-series
  [ICCV-2023] EMQ: Evolving Training-free Proxies for Automated Mixed Precision Quantization
  ☆26Updated last year
• andyrull / width-and-Depth-pruning-for-Vision-Transformer
  ☆19Updated 3 years ago
• wimh966 / outlier_suppression
  The official PyTorch implementation of the NeurIPS2022 (spotlight) paper, Outlier Suppression: Pushing the Limit of Low-bit Transformer L…
  ☆47Updated 2 years ago
• YanjingLi0202 / Q-ViT
  The official implementation of the NeurIPS 2022 paper Q-ViT.
  ☆89Updated 2 years ago
• GATECH-EIC / ShiftAddViT
  [NeurIPS 2023] ShiftAddViT: Mixture of Multiplication Primitives Towards Efficient Vision Transformer
  ☆32Updated last year
• zhexinli / Q-ViT-DeiT
  DeiT implementation for Q-ViT
  ☆25Updated last month
• MingSun-Tse / TPP
  [ICLR'23] Trainability Preserving Neural Pruning (PyTorch)
  ☆32Updated 2 years ago
• yaozhewei / HAP
  ☆43Updated last year
• 1hunters / LIMPQ
  Official implementation for ECCV 2022 paper LIMPQ - "Mixed-Precision Neural Network Quantization via Learned Layer-wise Importance"
  ☆54Updated 2 years ago