codecaution / EvoMoE
☆15Updated last year
Related projects: ⓘ
- ☆54Updated 2 months ago
- Mixture of Attention Heads☆36Updated last year
- Official code for "pi-Tuning: Transferring Multimodal Foundation Models with Optimal Multi-task Interpolation", ICML 2023.☆32Updated last year
- On the Effectiveness of Parameter-Efficient Fine-Tuning☆38Updated 10 months ago
- Code release for Deep Incubation (https://arxiv.org/abs/2212.04129)☆90Updated last year
- This pytorch package implements PLATON: Pruning Large Transformer Models with Upper Confidence Bound of Weight Importance (ICML 2022).☆39Updated last year
- [NeurIPS2023] Make Your Pre-trained Model Reversible: From Parameter to Memory Efficient Fine-Tuning☆28Updated last year
- Code for "ECoFLaP: Efficient Coarse-to-Fine Layer-Wise Pruning for Vision-Language Models" (ICLR 2024)☆15Updated 7 months ago
- [ICLR 2023] "Sparse MoE as the New Dropout: Scaling Dense and Self-Slimmable Transformers" by Tianlong Chen*, Zhenyu Zhang*, Ajay Jaiswal…☆42Updated last year
- [EVA ICLR'23; LARA ICML'22] Efficient attention mechanisms via control variates, random features, and importance sampling☆78Updated last year
- [NeurIPS 2022] Make Sharpness-Aware Minimization Stronger: A Sparsified Perturbation Approach -- Official Implementation☆40Updated last year
- This package implements THOR: Transformer with Stochastic Experts.☆60Updated 2 years ago
- Implementation of AAAI 2022 Paper: Go wider instead of deeper☆32Updated last year
- Representation Surgery for Multi-Task Model Merging. ICML, 2024.☆23Updated 3 weeks ago
- PyTorch implementation of "From Sparse to Soft Mixtures of Experts"☆38Updated last year
- Source code for IJCAI 2022 Long paper: Parameter-Efficient Sparsity for Large Language Models Fine-Tuning.☆13Updated 2 years ago
- [ACL 2023] Code for paper “Tailoring Instructions to Student’s Learning Levels Boosts Knowledge Distillation”(https://arxiv.org/abs/2305.…☆38Updated last year
- EfficientVLM: Fast and Accurate Vision-Language Models via Knowledge Distillation and Modal-adaptive Pruning (ACL 2023)☆19Updated last year
- Official Pytorch Implementation of Our Paper Accepted at ICLR 2024-- Dynamic Sparse No Training: Training-Free Fine-tuning for Sparse LLM…☆31Updated 5 months ago
- (CVPR 2022) Automated Progressive Learning for Efficient Training of Vision Transformers☆24Updated 2 years ago
- ☆20Updated last year
- [ICML 2024] CrossGET: Cross-Guided Ensemble of Tokens for Accelerating Vision-Language Transformers.☆23Updated 11 months ago
- [AAAI 2024] Fluctuation-based Adaptive Structured Pruning for Large Language Models☆34Updated 8 months ago
- [ICML 2024] Official code for the paper "Revisiting Zeroth-Order Optimization for Memory-Efficient LLM Fine-Tuning: A Benchmark ".☆62Updated 2 months ago
- AutoPEFT: Automatic Configuration Search for Parameter-Efficient Fine-Tuning (Zhou et al.; TACL)☆42Updated 6 months ago
- The source code of the EMNLP 2023 main conference paper: Sparse Low-rank Adaptation of Pre-trained Language Models.☆62Updated 6 months ago
- PyTorch codes for "LST: Ladder Side-Tuning for Parameter and Memory Efficient Transfer Learning"☆229Updated last year
- ☆25Updated 11 months ago
- Source code of EMNLP 2022 Findings paper "SparseAdapter: An Easy Approach for Improving the Parameter-Efficiency of Adapters"☆18Updated 5 months ago
- Metrics for "Beyond neural scaling laws: beating power law scaling via data pruning " (NeurIPS 2022 Outstanding Paper Award)☆51Updated last year