ksreenivasan / pruning_is_enough
Pruning is all you need (hopefully)
☆11Updated 2 years ago
Alternatives and similar repositories for pruning_is_enough
Users that are interested in pruning_is_enough are comparing it to the libraries listed below
Sorting:
- Code release for REPAIR: REnormalizing Permuted Activations for Interpolation Repair☆47Updated last year
- Identify a binary weight or binary weight and activation subnetwork within a randomly initialized network by only pruning and binarizing …☆52Updated 3 years ago
- Code accompanying the NeurIPS 2020 paper: WoodFisher (Singh & Alistarh, 2020)☆50Updated 4 years ago
- PyTorch implementation of LARS (Layer-wise Adaptive Rate Scaling)☆20Updated 6 years ago
- ☆45Updated 4 years ago
- ☆35Updated 2 years ago
- [ICLR 2023] "Sparsity May Cry: Let Us Fail (Current) Sparse Neural Networks Together!" Shiwei Liu, Tianlong Chen, Zhenyu Zhang, Xuxi Chen…☆28Updated last year
- Good Subnetworks Provably Exist: Pruning via Greedy Forward Selection☆21Updated 4 years ago
- Revisiting Efficient Training Algorithms For Transformer-based Language Models (NeurIPS 2023)☆80Updated last year
- Lightweight torch implementation of rigl, a sparse-to-sparse optimizer.☆56Updated 3 years ago
- Git Re-Basin: Merging Models modulo Permutation Symmetries in PyTorch☆75Updated 2 years ago
- Comparison of method "Pruning at initialization prior to training" (Synflow/SNIP/GraSP) in PyTorch☆16Updated last year
- Train ImageNet *fast* in 500 lines of code with FFCV☆142Updated last year
- A generic code base for neural network pruning, especially for pruning at initialization.☆30Updated 2 years ago
- Efficient Riemannian Optimization on Stiefel Manifold via Cayley Transform☆40Updated 6 years ago
- [ICML 2021] "Do We Actually Need Dense Over-Parameterization? In-Time Over-Parameterization in Sparse Training" by Shiwei Liu, Lu Yin, De…☆45Updated last year
- [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
- [IJCAI'22 Survey] Recent Advances on Neural Network Pruning at Initialization.☆59Updated last year
- Spartan is an algorithm for training sparse neural network models. This repository accompanies the paper "Spartan Differentiable Sparsity…☆24Updated 2 years ago
- ☆53Updated 7 months ago
- ☆14Updated 4 years ago
- Soft Threshold Weight Reparameterization for Learnable Sparsity☆89Updated 2 years ago
- Prospect Pruning: Finding Trainable Weights at Initialization Using Meta-Gradients☆31Updated 3 years ago
- Sharpness-Aware Minimization Leads to Low-Rank Features [NeurIPS 2023]☆28Updated last year
- ☆10Updated 3 years ago
- ☆67Updated 5 months ago
- Code for Sanity-Checking Pruning Methods: Random Tickets can Win the Jackpot☆42Updated 4 years ago
- Implementation of Continuous Sparsification, a method for pruning and ticket search in deep networks☆33Updated 2 years ago
- Code for "Picking Winning Tickets Before Training by Preserving Gradient Flow" https://openreview.net/pdf?id=SkgsACVKPH☆104Updated 5 years ago
- [ICLR2023] NTK-SAP: Improving neural network pruning by aligning training dynamics☆18Updated 2 years ago