Stars
[CVPR'24 Spotlight] The official implementation of "State Space Models for Event Cameras"
A curated list of resources for using LLMs to develop more competitive grant applications.
Introducing dendrites to spiking neural networks. Designed for the Brian 2 simulator.
Improved Implementation of "Can Forward Gradient Match Backpropagation?" (ICML, 2023)
Parallelizing non-linear sequential models over the sequence length
AutoGPT is the vision of accessible AI for everyone, to use and to build on. Our mission is to provide the tools, so that you can focus on what matters.
Unofficial implementation of MLP-Mixer: An all-MLP Architecture for Vision
PyTorch implementation of Mixer-nano (#parameters is 0.67M, originally Mixer-S/16 has 18M) with 90.83 % acc. on CIFAR-10. Training from scratch.
🦁 Lion, new optimizer discovered by Google Brain using genetic algorithms that is purportedly better than Adam(w), in Pytorch
Template that combines PyTorch Lightning and Hydra
Awesome Incremental Learning
TensorFlow on mobile with speech-to-text DL models.
Some of the fine books I have read.
Demo for PyTorch Lite on Android for an article I wrote on Medium
Training RNNs as Fast as CNNs (https://arxiv.org/abs/1709.02755)
FeedForward Propagation Through Time on Spiking Neural Network (SNNs)
RWKV is an RNN with transformer-level LLM performance. It can be directly trained like a GPT (parallelizable). So it's combining the best of RNN and transformer - great performance, fast inference,…
Accurate and efficient Spiking recurrent networks on ECG,SHD,SSC,SOLI,(p)SMNIST,TIMIT
Pytorch library for fast transformer implementations
Training Recurrent Neural Networks via Forward Propagation Through Time
这是一个YoloV4-tiny-pytorch的源码，可以用于训练自己的模型。