Alternatives and similar repositories for bitprune

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

• HuangOwen / QAT-ACS
  [TMLR] Official PyTorch implementation of paper "Efficient Quantization-aware Training with Adaptive Coreset Selection"
  ☆32Updated 9 months ago
• iamkanghyunchoi / ait
  It's All In the Teacher: Zero-Shot Quantization Brought Closer to the Teacher [CVPR 2022 Oral]
  ☆29Updated 2 years ago
• Jangho-Kim / PSG-pytorch
  Position-based Scaled Gradient for Model Quantization and Pruning Code (NeurIPS 2020)
  ☆26Updated 4 years ago
• 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
• lliai / EMQ-series
  [ICCV-2023] EMQ: Evolving Training-free Proxies for Automated Mixed Precision Quantization
  ☆26Updated last year
• yaozhewei / HAP
  ☆43Updated last year
• hfutqian / AdaDFQ
  ☆22Updated 7 months ago
• 1hunters / LIMPQ
  Official implementation for ECCV 2022 paper LIMPQ - "Mixed-Precision Neural Network Quantization via Learned Layer-wise Importance"
  ☆54Updated 2 years ago
• MingSun-Tse / TPP
  [ICLR'23] Trainability Preserving Neural Pruning (PyTorch)
  ☆32Updated 2 years ago
• jaeho-lee / layer-adaptive-sparsity
  In progress.
  ☆64Updated last year
• MAC-AutoML / OMPQ
  ☆25Updated 3 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
• peiswang / BitSplit
  BitSplit Post-trining Quantization
  ☆50Updated 3 years ago
• 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
• lihuantong / HAST
  ☆12Updated last year
• zysxmu / DFSQ
  super-resolution; post-training quantization; model compression
  ☆12Updated last year
• 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
• WeixiangXu / STTN
  ☆17Updated 2 years ago
• iamkanghyunchoi / qimera
  Qimera: Data-free Quantization with Synthetic Boundary Supporting Samples [NeurIPS 2021]
  ☆32Updated 3 years ago
• shawnricecake / search-llm
  [NeurIPS 2024] Search for Efficient LLMs
  ☆14Updated 4 months ago
• nbasyl / OFQ
  The official implementation of the ICML 2023 paper OFQ-ViT
  ☆30Updated last year
• hikvision-research / SAViT
  ☆12Updated last year
• zyxxmu / White-Box
  Pytorch implementation of our paper accepted by IEEE TNNLS, 2022 — Carrying out CNN Channel Pruning in a White Box
  ☆18Updated 3 years ago
• bytedance / MRECG
  ☆34Updated 2 years ago
• hustvl / PD-Quant
  [CVPR 2023] PD-Quant: Post-Training Quantization Based on Prediction Difference Metric
  ☆56Updated 2 years ago
• selkerdawy / FTWT
  Fire Together Wire Together: A Dynamic Pruning Approach with Self-Supervised Mask Prediction
  ☆11Updated 3 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
• Daner-Wang / VTC-LFC
  ☆27Updated 2 years ago
• 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
• Yu-Zhewen / SVD-NAS
  ☆11Updated 2 years ago