Popular GitHub Repositories for Dot

.NET, Angular, Clean Architecture, Clean Code, SOLID Principles, KISS Principle, DRY Principle, Fail Fast Principle, Common Closure Principle, Common Reuse Principle, Acyclic Dependencies Principle, Mediator Pattern, Result Pattern, Folder-by-Feature Structure, Separation of Concerns

TensorFlow API for .NET languages

High-level diagram representations for code

The official implementation of [CVPR2022] Decoupled Knowledge Distillation https://arxiv.org/abs/2203.08679 and [ICCV2023] DOT: A Distillation-Oriented Trainer https://openaccess.thecvf.com/content/ICCV2023/papers/Zhao_DOT_A_Distillation-Oriented_Trainer_ICCV_2023_paper.pdf

Score documents using embedding-vectors dot-product or cosine-similarity with ES Lucene engine

LV-DOT: LiDAR-Visual Dynamic Obstacle Detection and Tracking (C++/Python/ROS)

Fast, comprehensive DNS performance testing with DNSSEC validation, DoH/DoT support, and enterprise features

This repository contain various types of attention mechanism like Bahdanau , Soft attention , Additive Attention , Hierarchical Attention etc in Pytorch, Tensorflow, Keras

several types of attention modules written in PyTorch for learning purposes

smart-ai-samples

An open-source .NET SDK for Google Gemini AI – Unified access to text, vision, chat, and embedding APIs.

This project aims to implement the Scaled-Dot-Product Attention layer and the Multi-Head Attention layer using various Positional Encoding methods.

INSYDE (Intelligent System Designer): An integrated enviroment to make your own intelligent systems.

LEAP: Linear Explainable Attention in Parallel for causal language modeling with O(1) path length, and O(1) inference

Term Frequency - Inverse Document Frequency and Cosine Similarity, used to check how similar two given texts are.

A "helper" to the surviv.io game, using machine learning

TextComposerLib contains many integrating classes to implement structured text generation tasks using various methods of procedural composition of text; ranging from simple text concatenation to complex code library construction.

This neural network is designed to be able to take an 20px-by-20px gray-scale image and detect whether the input image contains either a rectangle or a circle.

A simple and efficient command-line chatbot built using the Groq API and LLaMA 3.3-70B Versatile model. This project allows users to interact with a powerful large language model directly from the terminal.

llama 3.2 1b fp16 cpu inference in one file of pure VB.NET