VITA-Group / BackRazor_Neurips22
[Neurips 2022] “ Back Razor: Memory-Efficient Transfer Learning by Self-Sparsified Backpropogation”, Ziyu Jiang*, Xuxi Chen*, Xueqin Huang, Xianzhi Du, Denny Zhou, Zhangyang Wang
☆19Updated 2 years ago
Alternatives and similar repositories for BackRazor_Neurips22:
Users that are interested in BackRazor_Neurips22 are comparing it to the libraries listed below
- Official Pytorch Implementation of Our Paper Accepted at ICLR 2024-- Dynamic Sparse No Training: Training-Free Fine-tuning for Sparse LLM…☆45Updated 11 months ago
- Towards Meta-Pruning via Optimal Transport, ICLR 2024 (Spotlight)☆16Updated 3 months ago
- [ICLR 2022] "Unified Vision Transformer Compression" by Shixing Yu*, Tianlong Chen*, Jiayi Shen, Huan Yuan, Jianchao Tan, Sen Yang, Ji Li…☆52Updated last year
- [NeurIPS'21] "Chasing Sparsity in Vision Transformers: An End-to-End Exploration" by Tianlong Chen, Yu Cheng, Zhe Gan, Lu Yuan, Lei Zhang…☆89Updated last year
- ☆43Updated last year
- [ICLR'23] Trainability Preserving Neural Pruning (PyTorch)☆32Updated last year
- [ICML 2024] CrossGET: Cross-Guided Ensemble of Tokens for Accelerating Vision-Language Transformers.☆31Updated 2 months ago
- BESA is a differentiable weight pruning technique for large language models.☆14Updated last year
- ☆50Updated last year
- [ICCV 23]An approach to enhance the efficiency of Vision Transformer (ViT) by concurrently employing token pruning and token merging tech…☆93Updated last year
- Code release for Deep Incubation (https://arxiv.org/abs/2212.04129)☆90Updated 2 years ago
- [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
- The official implementation of "2024NeurIPS Dynamic Tuning Towards Parameter and Inference Efficiency for ViT Adaptation"☆42Updated 2 months ago
- (CVPR 2022) Automated Progressive Learning for Efficient Training of Vision Transformers☆25Updated 3 weeks ago
- [NeurIPS 2024] Search for Efficient LLMs☆12Updated 2 months ago
- Code for ViTAS_Vision Transformer Architecture Search☆52Updated 3 years ago
- Metrics for "Beyond neural scaling laws: beating power law scaling via data pruning " (NeurIPS 2022 Outstanding Paper Award)☆55Updated last year
- [NeurIPS'22] What Makes a "Good" Data Augmentation in Knowledge Distillation -- A Statistical Perspective☆36Updated 2 years ago
- [NeurIPS 2023] ShiftAddViT: Mixture of Multiplication Primitives Towards Efficient Vision Transformer☆32Updated last year
- ☆12Updated last year
- [ICML 2024] SPP: Sparsity-Preserved Parameter-Efficient Fine-Tuning for Large Language Models☆18Updated 9 months ago
- [NeurIPS‘2021] "MEST: Accurate and Fast Memory-Economic Sparse Training Framework on the Edge", Geng Yuan, Xiaolong Ma, Yanzhi Wang et al…☆18Updated 3 years ago
- The official implementation of the ICML 2023 paper OFQ-ViT☆30Updated last year
- This repository is the implementation of the paper Training Free Pretrained Model Merging (CVPR2024).☆29Updated last year
- Code for ECCV 2022 paper “Learning with Recoverable Forgetting”☆21Updated 2 years ago
- It's All In the Teacher: Zero-Shot Quantization Brought Closer to the Teacher [CVPR 2022 Oral]☆29Updated 2 years ago
- The code repository of "MBQ: Modality-Balanced Quantization for Large Vision-Language Models"☆35Updated this week
- ☆36Updated 2 years ago
- ICLR 2024, Towards Lossless Dataset Distillation via Difficulty-Aligned Trajectory Matching☆102Updated 9 months ago
- [CVPR 2025] Q-DiT: Accurate Post-Training Quantization for Diffusion Transformers☆40Updated 6 months ago