Multi-Attention-Network

Implementation of Vision Transformer, a simple way to achieve SOTA in vision classification with only a single transformer encoder, in Pytorch

RWKV (pronounced RwaKuv) is an RNN with great LLM performance, which can also be directly trained like a GPT transformer (parallelizable). We are at RWKV-7 "Goose". So it's combining the best of RNN and transformer - great performance, linear time, constant space (no kv-cache), fast training, infinite ctx_len, and free sentence embedding.

Implementation / replication of DALL-E, OpenAI's Text to Image Transformer, in Pytorch

A concise but complete full-attention transformer with a set of promising experimental features from various papers

GDAL is an open source MIT licensed translator library for raster and vector geospatial data formats.

Long list of geospatial tools and resources

?? List of satellite image training datasets with annotations for computer vision and deep learning

TorchGeo: datasets, samplers, transforms, and pre-trained models for geospatial data

Graph Attention Networks (https://arxiv.org/abs/1710.10903)

Pytorch implementation of the Graph Attention Network model by Veličković et. al (2017, https://arxiv.org/abs/1710.10903)