OPTML-Group / DeepZeroLinks
[ICLR'24] "DeepZero: Scaling up Zeroth-Order Optimization for Deep Model Training" by Aochuan Chen*, Yimeng Zhang*, Jinghan Jia, James Diffenderfer, Jiancheng Liu, Konstantinos Parasyris, Yihua Zhang, Zheng Zhang, Bhavya Kailkhura, Sijia Liu
☆59Updated 8 months ago
Alternatives and similar repositories for DeepZero
Users that are interested in DeepZero are comparing it to the libraries listed below
Sorting:
- [ICML 2024] Official code for the paper "Revisiting Zeroth-Order Optimization for Memory-Efficient LLM Fine-Tuning: A Benchmark ".☆105Updated 11 months ago
- Second-Order Fine-Tuning without Pain for LLMs: a Hessian Informed Zeroth-Order Optimizer☆15Updated 4 months ago
- SLTrain: a sparse plus low-rank approach for parameter and memory efficient pretraining (NeurIPS 2024)☆31Updated 7 months ago
- Efficient Expert Pruning for Sparse Mixture-of-Experts Language Models: Enhancing Performance and Reducing Inference Costs☆19Updated 6 months ago
- Official Pytorch Implementation of Our Paper Accepted at ICLR 2024-- Dynamic Sparse No Training: Training-Free Fine-tuning for Sparse LLM…☆47Updated last year
- ☆13Updated last year
- ☆57Updated last year
- ☆36Updated 2 years ago
- Sharpness-Aware Minimization Leads to Low-Rank Features [NeurIPS 2023]☆28Updated last year
- This is the official implementation of the ICML 2023 paper - Can Forward Gradient Match Backpropagation ?☆12Updated 2 years ago
- ☆55Updated 6 months ago
- Awesome-Low-Rank-Adaptation☆104Updated 8 months ago
- AdaMerging: Adaptive Model Merging for Multi-Task Learning. ICLR, 2024.☆83Updated 7 months ago
- [NeurIPS 2024 Spotlight] EMR-Merging: Tuning-Free High-Performance Model Merging☆59Updated 3 months ago
- A curated list of Model Merging methods.☆92Updated 9 months ago
- [EMNLP 24] Source code for paper 'AdaZeta: Adaptive Zeroth-Order Tensor-Train Adaption for Memory-Efficient Large Language Models Fine-Tu…☆11Updated 6 months ago
- [NeurIPS 2023 Spotlight] Temperature Balancing, Layer-wise Weight Analysis, and Neural Network Training☆35Updated 2 months ago
- [NAACL 24 Oral] LoRETTA: Low-Rank Economic Tensor-Train Adaptation for Ultra-Low-Parameter Fine-Tuning of Large Language Models☆35Updated 5 months ago
- Compressible Dynamics in Deep Overparameterized Low-Rank Learning & Adaptation (ICML'24 Oral)☆13Updated 11 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
- [TPAMI 2023] Low Dimensional Landscape Hypothesis is True: DNNs can be Trained in Tiny Subspaces☆42Updated 2 years ago
- LoRA-XS: Low-Rank Adaptation with Extremely Small Number of Parameters☆35Updated 3 months ago
- [ICML2022] Training Your Sparse Neural Network Better with Any Mask. Ajay Jaiswal, Haoyu Ma, Tianlong Chen, ying Ding, and Zhangyang Wang☆28Updated 2 years ago
- A generic code base for neural network pruning, especially for pruning at initialization.☆30Updated 2 years ago
- [ICML 2024 Oral] This project is the official implementation of our Accurate LoRA-Finetuning Quantization of LLMs via Information Retenti…☆65Updated last year
- Activation-aware Singular Value Decomposition for Compressing Large Language Models☆71Updated 8 months ago
- Code for the paper: Why Transformers Need Adam: A Hessian Perspective☆59Updated 3 months ago
- Deep Learning & Information Bottleneck☆60Updated last year
- Official repository of "Localizing Task Information for Improved Model Merging and Compression" [ICML 2024]☆45Updated 8 months ago
- LISA: Layerwise Importance Sampling for Memory-Efficient Large Language Model Fine-Tuning☆31Updated last year