ziplab / SAQLinks
This is the official PyTorch implementation for "Sharpness-aware Quantization for Deep Neural Networks".
☆43Updated 3 years ago
Alternatives and similar repositories for SAQ
Users that are interested in SAQ are comparing it to the libraries listed below
Sorting:
- [NeurIPS'21] "Chasing Sparsity in Vision Transformers: An End-to-End Exploration" by Tianlong Chen, Yu Cheng, Zhe Gan, Lu Yuan, Lei Zhang…☆90Updated last year
- ☆17Updated 2 years ago
- Qimera: Data-free Quantization with Synthetic Boundary Supporting Samples [NeurIPS 2021]☆33Updated 3 years ago
- An official implementation of "Network Quantization with Element-wise Gradient Scaling" (CVPR 2021) in PyTorch.☆94Updated last year
- [ICLR 2022] "Unified Vision Transformer Compression" by Shixing Yu*, Tianlong Chen*, Jiayi Shen, Huan Yuan, Jianchao Tan, Sen Yang, Ji Li…☆53Updated last year
- This is the pytorch implementation for the paper: Generalizable Mixed-Precision Quantization via Attribution Rank Preservation, which is…☆25Updated 3 years ago
- official implementation of Generative Low-bitwidth Data Free Quantization(GDFQ)☆54Updated last year
- In progress.☆64Updated last year
- Collections of model quantization algorithms. Any issues, please contact Peng Chen (blueardour@gmail.com)☆71Updated 3 years ago
- ☆43Updated last year
- 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
- ☆25Updated 3 years ago
- Position-based Scaled Gradient for Model Quantization and Pruning Code (NeurIPS 2020)☆26Updated 4 years ago
- Pytorch implementation of our paper accepted by TPAMI 2023 — Lottery Jackpots Exist in Pre-trained Models☆34Updated 2 years ago
- PyTorch implementation of Towards Efficient Training for Neural Network Quantization☆15Updated 5 years ago
- [ICLR'23] Trainability Preserving Neural Pruning (PyTorch)☆33Updated 2 years ago
- Post-training sparsity-aware quantization☆34Updated 2 years ago
- Pytorch implementation of our paper accepted by IEEE TNNLS, 2022 — Carrying out CNN Channel Pruning in a White Box☆18Updated 3 years ago
- Code for ICML 2021 submission☆34Updated 4 years ago
- Code for our ICLR'2022 paper "Generalizing Few-Shot NAS with Gradient Matching"☆22Updated 2 years ago
- It's All In the Teacher: Zero-Shot Quantization Brought Closer to the Teacher [CVPR 2022 Oral]☆29Updated 2 years ago
- [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
- Pytorch implementation of our paper accepted by CVPR 2022 -- IntraQ: Learning Synthetic Images with Intra-Class Heterogeneity for Zero-Sh…☆33Updated 3 years ago
- [TMLR] Official PyTorch implementation of paper "Efficient Quantization-aware Training with Adaptive Coreset Selection"☆33Updated 10 months ago
- How Do Adam and Training Strategies Help BNNs Optimization? In ICML 2021.☆60Updated 4 years ago
- [ICLR 2021 Spotlight] "CPT: Efficient Deep Neural Network Training via Cyclic Precision" by Yonggan Fu, Han Guo, Meng Li, Xin Yang, Yinin…☆31Updated last year
- code for "AttentiveNAS Improving Neural Architecture Search via Attentive Sampling"☆104Updated 3 years ago
- ☆17Updated 2 years ago
- [CVPRW 21] "BNN - BN = ? Training Binary Neural Networks without Batch Normalization", Tianlong Chen, Zhenyu Zhang, Xu Ouyang, Zechun Liu…☆57Updated 3 years ago
- BitSplit Post-trining Quantization☆50Updated 3 years ago