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Neighborhood Attention Transformer, arxiv 2022 / CVPR 2023. Dilated Neighborhood Attention Transformer, arxiv 2022
🏆 A ranked list of awesome python developer tools and libraries. Updated weekly.
fabric is an open-source framework for augmenting humans using AI. It provides a modular framework for solving specific problems using a crowdsourced set of AI prompts that can be used anywhere.
A Supervised and Semi-Supervised Object Detection Library for YOLO Series
A content-first, sliding sidebar theme for Jekyll.
Build a Jekyll blog in minutes, without touching the command line.
AgML is a centralized framework for agricultural machine learning. AgML provides access to public agricultural datasets for common agricultural deep learning tasks, with standard benchmarks and pre…
In this repository using the sparse training, group channel pruning and knowledge distilling for YOLOV4,
Solve puzzles. Improve your pytorch.
🐶 A tool to package, serve, and deploy any ML model on any platform. Archived to be resurrected one day🤞
A playbook for systematically maximizing the performance of deep learning models.
Official codes of ICCV2023 paper: <<FemtoDet: an object detection baseline for energy versus performance tradeoffs>>
NanoDet-Plus⚡Super fast and lightweight anchor-free object detection model. 🔥Only 980 KB(int8) / 1.8MB (fp16) and run 97FPS on cellphone🔥
A repository in preparation for open-sourcing lottery ticket hypothesis code.
A framework to enable multimodal models to operate a computer.
This repository contains a Pytorch implementation of the paper "The Lottery Ticket Hypothesis: Finding Sparse, Trainable Neural Networks" by Jonathan Frankle and Michael Carbin that can be easily a…
FCOS: Fully Convolutional One-Stage Object Detection (ICCV'19)
Semantic segmentation models with 500+ pretrained convolutional and transformer-based backbones.
PyTorch ,ONNX and TensorRT implementation of YOLOv4
Efficient computing methods developed by Huawei Noah's Ark Lab
Reduce end to end training time from days to hours (or hours to minutes), and energy requirements/costs by an order of magnitude using coresets and data selection.
This repository provides code for machine learning algorithms for edge devices developed at Microsoft Research India.