In the OmniQuant pipeline, SpikeLLM significantly reduces 25.51% WikiText2 perplexity and improves 3.08% average accuracy of 6 zero-shot datasets on a LLAMA2-7B 4A4W model. In the GPTQ pipeline, SpikeLLM realizes a sparse ternary quantization, which achieves additive in all linear layers. ...
SpikingJelly是一个基于PyTorch,使用脉冲神经网络(Spiking Neural Network, SNN)进行深度学习的框架。 SpikingJelly的文档使用中英双语编写:https://spikingjelly.readthedocs.io。 安装 以前所未有的简单方式搭建SNN 快速好用的ANN-SNN转换 CUDA增强的神经元 设备支持 ...
Spiking neural network simulator This project is written in C, parallelised with OpenMP and requires theGNU Scientific Library(for pseudo RNGs). Data analysis is conducted with the accompanying Matlab files. It was developed under OS X and includes Xcode project files and a Makefile. ...
Please refer to thewiki tabfor additional ablation studies. Acknowledgements These works were supported by the Australian Government, Intel Labs, and the Queensland University of Technology (QUT) through the Centre for Robotics.
The Bee simulator is an open source Spiking Neural Network (SNN) simulator, freely available, specialised in Liquid State Machine (LSM) systems with its core functions fully implemented in C. It was developed together with my PhD thesis (you can see where it was used in my publications) excl...
CARLsim is an efficient, easy-to-use, GPU-accelerated library for simulating large-scale spiking neural network (SNN) models with a high degree of biological detail. CARLsim allows execution of networks of Izhikevich spiking neurons with realistic synaptic dynamics on both generic x86 CPUs and stand...
我们采用的数据集是Alice's Adventures in Wonderland和Wikitext-2。我们首先缩小这些数据集,并通过将大写字母替换为小写来清除大写字母。经过上述预处理后,Alice's Adventures in Wonderland和Wikitext-2分别包含41个和74个不同的字符。并且它们都具有52000个字符总数。此数据集的测试数据集有所不同,具有相同的不同...
For learning weight (delay learning not yet implemented) parameters of a multilayer spiking neural network. Natively handles multiple spikes in each layer and error backpropagation through the layers. Version 0.1 Requirements Python 3 with the following packages installed: ...
We next tested for predictive relationships between neural activity and behavioral outcome. To assess detection-predictive effects independent of sensory effects, we compared stimulus amplitude matched hits and misses (Figures 5A–5C). First, we tested LFP power across frequency bands (Figures 5D, 5E...
Toolbox for converting analog to spiking neural networks (ANN to SNN), and running them in a spiking neuron simulator. - NeuromorphicProcessorProject/snn_toolbox