There are 3 repositories under transformer-architecture topic.
An ultimately comprehensive paper list of Vision Transformer/Attention, including papers, codes, and related websites
Inference Llama 2 in one file of pure 🔥
Self-contained Machine Learning and Natural Language Processing library in Go
Sequence-to-sequence framework with a focus on Neural Machine Translation based on PyTorch
Code for CRATE (Coding RAte reduction TransformEr).
Implementation of the Swin Transformer in PyTorch.
[BMVC 2022] You Only Need 90K Parameters to Adapt Light: A Light Weight Transformer for Image Enhancement and Exposure Correction. SOTA for low light enhancement, 0.004 seconds try this for pre-processing.
[ECCV 2022] Official repository for "MaxViT: Multi-Axis Vision Transformer". SOTA foundation models for classification, detection, segmentation, image quality, and generative modeling...
A novel implementation of fusing ViT with Mamba into a fast, agile, and high performance Multi-Modal Model. Powered by Zeta, the simplest AI framework ever.
[IGARSS'22]: A Transformer-Based Siamese Network for Change Detection
This repo contains the updated version of all the assignments/labs (done by me) of Deep Learning Specialization on Coursera by Andrew Ng. It includes building various deep learning models from scratch and implementing them for object detection, facial recognition, autonomous driving, neural machine translation, trigger word detection, etc.
IEEE TNNLS 2021, transformer, multi-graph transformer, graph, graph classification, sketch recognition, sketch classification, free-hand sketch, official code of the paper "Multi-Graph Transformer for Free-Hand Sketch Recognition"
PyContinual (An Easy and Extendible Framework for Continual Learning)
The repository of ET-BERT, a network traffic classification model on encrypted traffic. The work has been accepted as The Web Conference (WWW) 2022 accepted paper.
An Extensible Continual Learning Framework Focused on Language Models (LMs)
Seq2SeqSharp is a tensor based fast & flexible deep neural network framework written by .NET (C#). It has many highlighted features, such as automatic differentiation, different network types (Transformer, LSTM, BiLSTM and so on), multi-GPUs supported, cross-platforms (Windows, Linux, x86, x64, ARM), multimodal model for text and images and so on.
Fine-tuned pre-trained GPT2 for custom topic specific text generation. Such system can be used for Text Augmentation.
PyTorch implementation of the model presented in "Satellite Image Time Series Classification with Pixel-Set Encoders and Temporal Self-Attention"
Attention Is All You Need | a PyTorch Tutorial to Transformers
Notes about "Attention is all you need" video (https://www.youtube.com/watch?v=bCz4OMemCcA)
[MICCAI 2021] Boundary-aware Transformers for Skin Lesion Segmentation
A summarization of Transformer-based architectures for CV tasks, including image classification, object detection, segmentation, and Few-shot Learning. Keep updated frequently.
Implementation of Vision Transformer from scratch and performance compared to standard CNNs (ResNets) and pre-trained ViT on CIFAR10 and CIFAR100.
Basic Gesture Recognition Using mmWave Sensor - TI AWR1642
My implementation of "Algorithm of Thoughts: Enhancing Exploration of Ideas in Large Language Models"
Official implementation of "Particle Transformer for Jet Tagging".
Edge-Augmented Graph Transformer