haiquanlu / AlphaPruningLinks
[NeurIPS 2024] AlphaPruning: Using Heavy-Tailed Self Regularization Theory for Improved Layer-wise Pruning of Large Language Models
☆29Updated 6 months ago
Alternatives and similar repositories for AlphaPruning
Users that are interested in AlphaPruning are comparing it to the libraries listed below
Sorting:
- Data distillation benchmark☆71Updated 6 months ago
- Elucidated Dataset Condensation (NeurIPS 2024)☆20Updated last year
- [NeurIPS 2024 Spotlight] EMR-Merging: Tuning-Free High-Performance Model Merging☆74Updated 9 months ago
- Task Singular Vectors: Reducing Task Interference in Model Merging. Merge models avoiding task interference through separable models.☆38Updated this week
- Awesome-Low-Rank-Adaptation☆124Updated last year
- ☆61Updated last year
- CorDA: Context-Oriented Decomposition Adaptation of Large Language Models for task-aware parameter-efficient fine-tuning(NeurIPS 2024)☆53Updated 11 months ago
- [ICML'24 Oral] APT: Adaptive Pruning and Tuning Pretrained Language Models for Efficient Training and Inference☆46Updated last year
- LISA: Layerwise Importance Sampling for Memory-Efficient Large Language Model Fine-Tuning☆36Updated last year
- Code for paper "Merging Multi-Task Models via Weight-Ensembling Mixture of Experts"☆30Updated last year
- Official Pytorch Implementation of "Outlier-weighed Layerwise Sampling for LLM Fine-tuning" by Pengxiang Li, Lu Yin, Xiaowei Gao, Shiwei …☆35Updated 6 months ago
- The loss landscape of Large Language Models resemble basin!☆34Updated 5 months ago
- [CVPR2024 highlight] Generalized Large-Scale Data Condensation via Various Backbone and Statistical Matching (G-VBSM)☆28Updated last year
- ☆23Updated last year
- Official Pytorch Implementation of Our Paper Accepted at ICLR 2024-- Dynamic Sparse No Training: Training-Free Fine-tuning for Sparse LLM…☆50Updated last year
- ☆28Updated last year
- [CVPR 2024] On the Diversity and Realism of Distilled Dataset: An Efficient Dataset Distillation Paradigm☆80Updated 9 months ago
- A generalized framework for subspace tuning methods in parameter efficient fine-tuning.☆163Updated 5 months ago
- A curated list of Model Merging methods.☆94Updated 2 weeks ago
- [NeurIPS'25] dKV-Cache: The Cache for Diffusion Language Models☆123Updated 6 months ago
- [EMNLP 2023, Main Conference] Sparse Low-rank Adaptation of Pre-trained Language Models☆85Updated last year
- AdaMerging: Adaptive Model Merging for Multi-Task Learning. ICLR, 2024.☆97Updated last year
- Code for paper "Parameter Efficient Multi-task Model Fusion with Partial Linearization"☆24Updated last year
- Code accompanying the paper "Massive Activations in Large Language Models"☆187Updated last year
- ICLR 2024, Towards Lossless Dataset Distillation via Difficulty-Aligned Trajectory Matching☆105Updated last year
- Official repository of "Localizing Task Information for Improved Model Merging and Compression" [ICML 2024]☆51Updated last year
- Official code for our paper, "LoRA-Pro: Are Low-Rank Adapters Properly Optimized? "☆138Updated 8 months ago
- A block pruning framework for LLMs.☆27Updated 7 months ago
- ☆14Updated 2 years ago
- One-shot Entropy Minimization☆187Updated 6 months ago