VainF / Isomorphic-Pruning
[ECCV 2024] Isomorphic Pruning for Vision Models
☆66Updated 8 months ago
Alternatives and similar repositories for Isomorphic-Pruning:
Users that are interested in Isomorphic-Pruning are comparing it to the libraries listed below
- [ICCV 23]An approach to enhance the efficiency of Vision Transformer (ViT) by concurrently employing token pruning and token merging tech…☆94Updated last year
- PyTorch code and checkpoints release for VanillaKD: https://arxiv.org/abs/2305.15781☆74Updated last year
- The official implementation of the NeurIPS 2022 paper Q-ViT.☆88Updated last year
- ☆44Updated last year
- ☆12Updated last year
- [CVPR-22] This is the official implementation of the paper "Adavit: Adaptive vision transformers for efficient image recognition".☆52Updated 2 years ago
- [TMLR] Official PyTorch implementation of paper "Quantization Variation: A New Perspective on Training Transformers with Low-Bit Precisio…☆43Updated 6 months ago
- Learnable Semi-structured Sparsity for Vision Transformers and Diffusion Transformers☆11Updated 2 months ago
- [CVPR 2024] PTQ4SAM: Post-Training Quantization for Segment Anything☆67Updated 9 months ago
- [NeurIPS 2023] Structural Pruning for Diffusion Models☆186Updated 9 months ago
- Official PyTorch implementation of Which Tokens to Use? Investigating Token Reduction in Vision Transformers presented at ICCV 2023 NIVT …☆35Updated last year
- [CVPR 2023] Castling-ViT: Compressing Self-Attention via Switching Towards Linear-Angular Attention During Vision Transformer Inference☆30Updated last year
- Training ImageNet / CIFAR models with sota strategies and fancy techniques such as ViT, KD, Rep, etc.☆82Updated last year
- It's All In the Teacher: Zero-Shot Quantization Brought Closer to the Teacher [CVPR 2022 Oral]☆29Updated 2 years ago
- In progress.☆63Updated last year
- The official implementation of "2024NeurIPS Dynamic Tuning Towards Parameter and Inference Efficiency for ViT Adaptation"☆44Updated 3 months ago
- [ICLR 2024 Spotlight] This is the official PyTorch implementation of "EfficientDM: Efficient Quantization-Aware Fine-Tuning of Low-Bit Di…☆59Updated 10 months ago
- 1.5−3.0× lossless training or pre-training speedup. An off-the-shelf, easy-to-implement algorithm for the efficient training of foundatio…☆220Updated 7 months ago
- Join the High Accuracy Club on ImageNet with A Binary Neural Network Ticket☆67Updated 2 years ago
- [CVPR 2023] PD-Quant: Post-Training Quantization Based on Prediction Difference Metric☆53Updated 2 years ago
- [CVPR 2025] Q-DiT: Accurate Post-Training Quantization for Diffusion Transformers☆45Updated 7 months ago
- The official implementation of LumiNet: The Bright Side of Perceptual Knowledge Distillation https://arxiv.org/abs/2310.03669☆19Updated last year
- [ICLR'23] Trainability Preserving Neural Pruning (PyTorch)☆33Updated last year
- Official PyTorch Code for "Is Synthetic Data From Diffusion Models Ready for Knowledge Distillation?" (https://arxiv.org/abs/2305.12954)☆46Updated last year
- [ICCV 2023] Efficient Joint Optimization of Layer-Adaptive Weight Pruning in Deep Neural Networks☆23Updated last year
- The codebase for paper "PPT: Token Pruning and Pooling for Efficient Vision Transformer"☆22Updated 5 months ago
- Official implementation of paper "Masked Distillation with Receptive Tokens", ICLR 2023.☆69Updated 2 years ago
- ☆21Updated last year
- (ICLR 2025) BinaryDM: Accurate Weight Binarization for Efficient Diffusion Models☆19Updated 6 months ago
- The official implementation of the ICML 2023 paper OFQ-ViT☆30Updated last year