Alternatives and similar repositories for qimera

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

• iamkanghyunchoi / ait
  It's All In the Teacher: Zero-Shot Quantization Brought Closer to the Teacher [CVPR 2022 Oral]
  ☆29Updated 2 years ago
• zysxmu / FDDA
  Pytorch implementation of our paper accepted by ECCV 2022-- Fine-grained Data Distribution Alignment for Post-Training Quantization
  ☆15Updated 2 years ago
• SHI-Labs / Any-Precision-DNNs
  Any-Precision Deep Neural Networks (AAAI 2021)
  ☆60Updated 5 years ago
• xushoukai / GDFQ
  official implementation of Generative Low-bitwidth Data Free Quantization(GDFQ)
  ☆54Updated last year
• yaozhewei / HAP
  ☆43Updated last year
• IST-DASLab / spdy
  Code for ICML 2022 paper "SPDY: Accurate Pruning with Speedup Guarantees"
  ☆19Updated 2 years ago
• MAC-AutoML / OMPQ
  ☆25Updated 3 years ago
• GATECH-EIC / Double-Win-Quant
  [ICML 2021] "Double-Win Quant: Aggressively Winning Robustness of Quantized DeepNeural Networks via Random Precision Training and Inferen…
  ☆14Updated 3 years ago
• GATECH-EIC / ShiftAddViT
  [NeurIPS 2023] ShiftAddViT: Mixture of Multiplication Primitives Towards Efficient Vision Transformer
  ☆31Updated last year
• lihuantong / HAST
  ☆12Updated last year
• VITA-Group / GraNet
  [Neurips 2021] Sparse Training via Boosting Pruning Plasticity with Neuroregeneration
  ☆31Updated 2 years ago
• deJQK / AdaBits
  ☆39Updated 2 years ago
• jaeho-lee / layer-adaptive-sparsity
  In progress.
  ☆65Updated last year
• ziplab / SAQ
  This is the official PyTorch implementation for "Sharpness-aware Quantization for Deep Neural Networks".
  ☆43Updated 3 years ago
• WeixiangXu / STTN
  ☆17Updated 2 years ago
• MingSun-Tse / TPP
  [ICLR'23] Trainability Preserving Neural Pruning (PyTorch)
  ☆33Updated 2 years ago
• nbasyl / OFQ
  The official implementation of the ICML 2023 paper OFQ-ViT
  ☆32Updated last year
• 1hunters / LIMPQ
  Official implementation for ECCV 2022 paper LIMPQ - "Mixed-Precision Neural Network Quantization via Learned Layer-wise Importance"
  ☆56Updated 2 years ago
• Qualcomm-AI-research / outlier-free-transformers
  ☆42Updated last year
• Qualcomm-AI-research / oscillations-qat
  ☆76Updated 2 years ago
• gilshm / sparq
  Post-training sparsity-aware quantization
  ☆34Updated 2 years ago
• MingSun-Tse / Awesome-Pruning-at-Initialization
  [IJCAI'22 Survey] Recent Advances on Neural Network Pruning at Initialization.
  ☆59Updated last year
• jmluu / Awesome-Efficient-Training
  A collection of research papers on efficient training of DNNs
  ☆70Updated 3 years ago
• jaewonalive / PeerAiD
  ☆22Updated last year
• RAIVNLab / STR
  Soft Threshold Weight Reparameterization for Learnable Sparsity
  ☆91Updated 2 years ago
• KwangHoonAn / PACT
  Reproducing Quantization paper PACT
  ☆64Updated 3 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
• HayeonLee / HELP
  Official PyTorch Implementation of HELP: Hardware-adaptive Efficient Latency Prediction for NAS via Meta-Learning (NeurIPS 2021 Spotlight…
  ☆63Updated 11 months ago
• MingSun-Tse / Smile-Pruning
  A generic code base for neural network pruning, especially for pruning at initialization.
  ☆30Updated 2 years ago
• yanghr / BSQ
  BSQ: Exploring Bit-Level Sparsity for Mixed-Precision Neural Network Quantization (ICLR 2021)
  ☆40Updated 4 years ago