Libraries for applying sparsification recipes to neural networks with a few lines of code, enabling faster and smaller models
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Updated
May 22, 2024 - Python
Libraries for applying sparsification recipes to neural networks with a few lines of code, enabling faster and smaller models
Experiments for channel-based Structured Pruning Adapters
A curated list for Efficient Large Language Models
[NAACL Findings 2024] Pruning as a Domain-specific LLM Extractor. Support LLaMA2.
[NeurIPS 2023] LLM-Pruner: On the Structural Pruning of Large Language Models. Support LLaMA, Llama-2, BLOOM, Vicuna, Baichuan, etc.
Official code for "EC-SNN: Splitting Deep Spiking Neural Networks on Edge Devices" (IJCAI2024)
Automated Identification of Redundant Layer Blocks for Pruning in Large Language Models
KEN: Unleash the power of large language models with the easiest and universal non-parametric pruning algorithm
Study and Implementation of various neural network pruning techniques. Extending the lottery ticket hypothesis to structured pruning for accelerated training while maintaining uncertainty and accuracy. The focus is on simplifying the model's complexity without sacrificing its overall performance or leading to overfitting.
[AAAI 2024] Fluctuation-based Adaptive Structured Pruning for Large Language Models
Java implementation of an automatic player for the Murus Gallicus game.
[JCST 2023] "Inductive Lottery Ticket Learning for Graph Neural Networks" by Yongduo Sui, Xiang Wang, Tianlong Chen, Meng Wang, Xiangnan He, Tat-Seng Chua.
This repository has the porpouse of give a solution to the travelling sales man problem
This repository contains scripts to prune Wav2vec2 using a neuroevolution-based method. More details about this method can be found in the paper Compressing Wav2vec2 for Embedded Applications.
Project code developed to accompany the thesis of the bachelor programme BSc Data Science and Artificial Intelligence taught @ Universiteit Maastricht. It consists in (re-)discovering Forbidden Minors for Treewidth, through a series of graph search/analysis techniques.
Model optimizer used in Adlik.
Predicting employee productivity using tree models (decision tree cassification, cross validation, minimal cost-complexity pruning, random forest)
A research library for pytorch-based neural network pruning, compression, and more.
Play the Othello board game against the algorithm and try to win!
Hierarchical Ensemble Pruning
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