SLDGroup / GradientFilter-CVPR23Links
☆13Updated 2 years ago
Alternatives and similar repositories for GradientFilter-CVPR23
Users that are interested in GradientFilter-CVPR23 are comparing it to the libraries listed below
Sorting:
- [Preprint] Why is the State of Neural Network Pruning so Confusing? On the Fairness, Comparison Setup, and Trainability in Network Prunin…☆41Updated 3 months ago
- EfficientVLM: Fast and Accurate Vision-Language Models via Knowledge Distillation and Modal-adaptive Pruning (ACL 2023)☆32Updated 2 years ago
- ☆26Updated 4 years ago
- Code for "ECoFLaP: Efficient Coarse-to-Fine Layer-Wise Pruning for Vision-Language Models" (ICLR 2024)☆20Updated last year
- [NeurIPS 2024] Search for Efficient LLMs☆15Updated 11 months ago
- BESA is a differentiable weight pruning technique for large language models.☆17Updated last year
- Official implement of Evo-ViT: Slow-Fast Token Evolution for Dynamic Vision Transformer☆74Updated 3 years ago
- [ICLR 2024] This is the official PyTorch implementation of "QLLM: Accurate and Efficient Low-Bitwidth Quantization for Large Language Mod…☆39Updated last year
- [ICCV-2023] EMQ: Evolving Training-free Proxies for Automated Mixed Precision Quantization☆28Updated 2 years ago
- PyTorch code and checkpoints release for VanillaKD: https://arxiv.org/abs/2305.15781☆76Updated 2 years ago
- The codebase for paper "PPT: Token Pruning and Pooling for Efficient Vision Transformer"☆28Updated last year
- [ICCV 23]An approach to enhance the efficiency of Vision Transformer (ViT) by concurrently employing token pruning and token merging tech…☆104Updated 2 years ago
- [ICLR 2024] This is the official PyTorch implementation of "QLLM: Accurate and Efficient Low-Bitwidth Quantization for Large Language Mod…☆30Updated last year
- ☆48Updated 2 years ago
- [ICLR'23] Trainability Preserving Neural Pruning (PyTorch)☆34Updated 2 years ago
- NAS Benchmark in "Prioritized Architecture Sampling with Monto-Carlo Tree Search", CVPR2021☆37Updated 4 years ago
- ☆36Updated 3 years ago
- ☆53Updated last year
- ☆28Updated 2 years ago
- [ICLR 2022] The Unreasonable Effectiveness of Random Pruning: Return of the Most Naive Baseline for Sparse Training by Shiwei Liu, Tianlo…☆77Updated 2 years ago
- It's All In the Teacher: Zero-Shot Quantization Brought Closer to the Teacher [CVPR 2022 Oral]☆29Updated 3 years ago
- [TMLR] Official PyTorch implementation of paper "Efficient Quantization-aware Training with Adaptive Coreset Selection"☆35Updated last year
- [ICML 2022] "DepthShrinker: A New Compression Paradigm Towards Boosting Real-Hardware Efficiency of Compact Neural Networks", by Yonggan …☆72Updated 3 years ago
- Learning Efficient Vision Transformers via Fine-Grained Manifold Distillation. NeurIPS 2022.☆32Updated 3 years ago
- [NeurIPS 2022] “M³ViT: Mixture-of-Experts Vision Transformer for Efficient Multi-task Learning with Model-Accelerator Co-design”, Hanxue …☆132Updated 3 years ago
- (CVPR 2022) Automated Progressive Learning for Efficient Training of Vision Transformers☆25Updated 9 months ago
- [AAAI 2024] Fluctuation-based Adaptive Structured Pruning for Large Language Models☆63Updated last year
- [CVPR-2022] Official implementation for "Knowledge Distillation with the Reused Teacher Classifier".☆100Updated 3 years ago
- [ICLR 2022] "Unified Vision Transformer Compression" by Shixing Yu*, Tianlong Chen*, Jiayi Shen, Huan Yuan, Jianchao Tan, Sen Yang, Ji Li…☆55Updated 2 years ago
- [ICML 2023] UPop: Unified and Progressive Pruning for Compressing Vision-Language Transformers☆105Updated 11 months ago