778 Repositories
Python post-training-quantization Libraries
Dataset and Code for the paper "DepthTrack: Unveiling the Power of RGBD Tracking" (ICCV2021), and "Depth-only Object Tracking" (BMVC2021)
DeT and DOT Code and datasets for "DepthTrack: Unveiling the Power of RGBD Tracking" (ICCV2021) "Depth-only Object Tracking" (BMVC2021) @InProceedings
ICCV2021, Tokens-to-Token ViT: Training Vision Transformers from Scratch on ImageNet
Tokens-to-Token ViT: Training Vision Transformers from Scratch on ImageNet, ICCV 2021 Update: 2021/03/11: update our new results. Now our T2T-ViT-14 w
A customisable game where you have to quickly click on black tiles in order of appearance while avoiding clicking on white squares.
W.I.P-Aim-Memory-Game A customisable game where you have to quickly click on black tiles in order of appearance while avoiding clicking on white squar
A simple code to fetch comments below an Instagram post and save them to a csv file
fetch_comments A simple code to fetch comments below an Instagram post and save them to a csv file usage First you have to enter your username and pas
Efficient Training of Audio Transformers with Patchout
PaSST: Efficient Training of Audio Transformers with Patchout This is the implementation for Efficient Training of Audio Transformers with Patchout Pa
This is the implementation of the paper LiST: Lite Self-training Makes Efficient Few-shot Learners.
LiST (Lite Self-Training) This is the implementation of the paper LiST: Lite Self-training Makes Efficient Few-shot Learners. LiST is short for Lite S
Open Source Discord bot with many cool features like Weather, Balance, Avatar, User, Server, RP-commands, Gif search, YouTube search, VK post search etc.
Сокобот Дискорд бот с открытым исходным кодом. Содержит в себе экономику, полезные команды (!аватар, !юзер, !сервер и тд.), рп-команды (!обнять, !глад
AWS Blog post code for running feature-extraction on images using AWS Batch and Cloud Development Kit (CDK).
Batch processing with AWS Batch and CDK Welcome This repository demostrates provisioning the necessary infrastructure for running a job on AWS Batch u
OCR Post Correction for Endangered Language Texts
📌 Coming soon: an update to the software including features from our paper on semi-supervised OCR post-correction, to be published in the Transaction
Self-supervised Product Quantization for Deep Unsupervised Image Retrieval - ICCV2021
Self-supervised Product Quantization for Deep Unsupervised Image Retrieval Pytorch implementation of SPQ Accepted to ICCV 2021 - paper Young Kyun Jang
Python functions to run WASS stereo wave processing executables, and load and post process WASS output files.
wass-pyfuns Python functions to run the WASS stereo wave processing executables, and load and post process the WASS output files. General WASS (Waves
A windows post exploitation tool that contains a lot of features for information gathering and more.
Crowbar - A windows post exploitation tool Status - ✔️ This project is now considered finished. Any updates from now on will most likely be new script
A Simple Framwork for CV Pre-training Model (SOCO, VirTex, BEiT)
A Simple Framwork for CV Pre-training Model (SOCO, VirTex, BEiT)
Efficient Sharpness-aware Minimization for Improved Training of Neural Networks
Efficient Sharpness-aware Minimization for Improved Training of Neural Networks Code for “Efficient Sharpness-aware Minimization for Improved Training
Code for EMNLP2021 paper "Allocating Large Vocabulary Capacity for Cross-lingual Language Model Pre-training"
VoCapXLM Code for EMNLP2021 paper Allocating Large Vocabulary Capacity for Cross-lingual Language Model Pre-training Environment DockerFile: dancingso
This bot will automatically like and follow users that post under a specified hashtag
Instagram-bot This bot will automatically like and follow users that post under a specified hashtag Dependencies Java JDK Selenium Updated version of
The spiritual successor to knockknock for PyTorch Lightning, get notified when your training ends
Who's there? The spiritual successor to knockknock for PyTorch Lightning, to get a notification when your training is complete or when it crashes duri
The Metabolomics Integrator (MINT) is a post-processing tool for liquid chromatography-mass spectrometry (LCMS) based metabolomics.
MINT (Metabolomics Integrator) The Metabolomics Integrator (MINT) is a post-processing tool for liquid chromatography-mass spectrometry (LCMS) based m
Revealing and Protecting Labels in Distributed Training
Revealing and Protecting Labels in Distributed Training
training script for space time memory network
Trainig Script for Space Time Memory Network This codebase implemented training code for Space Time Memory Network with some cyclic features. Requirem
Training Certifiably Robust Neural Networks with Efficient Local Lipschitz Bounds (Local-Lip)
Training Certifiably Robust Neural Networks with Efficient Local Lipschitz Bounds (Local-Lip) Introduction TL;DR: We propose an efficient and trainabl
This codebase facilitates fast experimentation of differentially private training of Hugging Face transformers.
private-transformers This codebase facilitates fast experimentation of differentially private training of Hugging Face transformers. What is this? Why
Coin-based opinion monitoring system
介绍 本仓库提供了基于币安 (Binance) 的二级市场舆情系统,可以根据自己的需求修改代码,设定各类告警提示 代码结构 binance.py - 与币安API交互 data_loader.py - 数据相关的读写 monitor.py - 监控的核心方法实现 analyze.py - 基于历史数
An API built to format given addresses using Python and Flask.
An API built to format given addresses using Python and Flask. About The API returns properly formatted data, i.e. removing duplicate fields, distingu
An interactive pygame implementation of quadtree spatial quantization
QuadTree-py An interactive pygame implementation of quadtree spatial quantization Contents Installation Usage API Reference TODO Installation Clone th
An application to see if your Ethereum staking validator(s) are members of the current or next post-Altair sync committees.
eth_sync_committee.py Since the Altair upgrade, 512 validators are randomly chosen every 256 epochs (~27 hours) to form a sync committee. Validators i
Enhancing Knowledge Tracing via Adversarial Training
Enhancing Knowledge Tracing via Adversarial Training This repository contains source code for the paper "Enhancing Knowledge Tracing via Adversarial T
SEC'21: Sparse Bitmap Compression for Memory-Efficient Training onthe Edge
Training Deep Learning Models on The Edge Training on the Edge enables continuous learning from new data for deployed neural networks on memory-constr
An Automated udemy coupons scraper which scrapes coupons and autopost the result in blogspot post
Autoscraper-n-blogger An Automated udemy coupons scraper which scrapes coupons and autopost the result in blogspot post and notifies via Telegram bot
Implementation of average- and worst-case robust flatness measures for adversarial training.
Relating Adversarially Robust Generalization to Flat Minima This repository contains code corresponding to the MLSys'21 paper: D. Stutz, M. Hein, B. S
A complete end-to-end machine learning portal that covers processes starting from model training to the model predicting results using FastAPI.
Machine Learning Portal Goal Application Workflow Process Design Live Project Goal A complete end-to-end machine learning portal that covers processes
Chinese NER(Named Entity Recognition) using BERT(Softmax, CRF, Span)
Chinese NER(Named Entity Recognition) using BERT(Softmax, CRF, Span)
Open source single image super-resolution toolbox containing various functionality for training a diverse number of state-of-the-art super-resolution models. Also acts as the companion code for the IEEE signal processing letters paper titled 'Improving Super-Resolution Performance using Meta-Attention Layers’.
Deep-FIR Codebase - Super Resolution Meta Attention Networks About This repository contains the main coding framework accompanying our work on meta-at
Implementation for On Provable Benefits of Depth in Training Graph Convolutional Networks
Implementation for On Provable Benefits of Depth in Training Graph Convolutional Networks Setup This implementation is based on PyTorch = 1.0.0. Smal
Colossal-AI: A Unified Deep Learning System for Large-Scale Parallel Training
ColossalAI An integrated large-scale model training system with efficient parallelization techniques. arXiv: Colossal-AI: A Unified Deep Learning Syst
A simple telegram bot to help you to remove forward tag from post from any messages . Maded in python3 using @Pyrogram . Developed by @Kunal-Diwan
Frwd-Tag-Remover Telegram Bot to Remove forward tag from any Post . If you need any more modes in repo or If you find out any bugs, mention in @Develo
Data, model training, and evaluation code for "PubTables-1M: Towards a universal dataset and metrics for training and evaluating table extraction models".
PubTables-1M This repository contains training and evaluation code for the paper "PubTables-1M: Towards a universal dataset and metrics for training a
Predicting lncRNA–protein interactions based on graph autoencoders and collaborative training
Predicting lncRNA–protein interactions based on graph autoencoders and collaborative training Code for our paper "Predicting lncRNA–protein interactio
Colossal-AI: A Unified Deep Learning System for Large-Scale Parallel Training
ColossalAI An integrated large-scale model training system with efficient parallelization techniques Installation PyPI pip install colossalai Install
A simple fun discord bot using discord.py that can post memes
A simple fun discord bot using discord.py * * Commands $commands - to see all commands $meme - for a random meme from the internet $cry - to make the
AugMax: Adversarial Composition of Random Augmentations for Robust Training
[NeurIPS'21] "AugMax: Adversarial Composition of Random Augmentations for Robust Training" by Haotao Wang, Chaowei Xiao, Jean Kossaifi, Zhiding Yu, Animashree Anandkumar, and Zhangyang Wang.
A quick and dirty script to scan the network, find default credentials on services and post a message to a Slack channel with the results.
A quick and dirty script to scan the network, find default credentials on services and post a message to a Slack channel with the results.
Exponential Graph is Provably Efficient for Decentralized Deep Training
Exponential Graph is Provably Efficient for Decentralized Deep Training This code repository is for the paper Exponential Graph is Provably Efficient
[NeurIPS'21] "AugMax: Adversarial Composition of Random Augmentations for Robust Training" by Haotao Wang, Chaowei Xiao, Jean Kossaifi, Zhiding Yu, Animashree Anandkumar, and Zhangyang Wang.
AugMax: Adversarial Composition of Random Augmentations for Robust Training Haotao Wang, Chaowei Xiao, Jean Kossaifi, Zhiding Yu, Anima Anandkumar, an
[NeurIPS 2021] Source code for the paper "Qu-ANTI-zation: Exploiting Neural Network Quantization for Achieving Adversarial Outcomes"
Qu-ANTI-zation This repository contains the code for reproducing the results of our paper: Qu-ANTI-zation: Exploiting Quantization Artifacts for Achie
In this project I played with mlflow, streamlit and fastapi to create a training and prediction app on digits
Fastapi + MLflow + streamlit Setup env. I hope I covered all. pip install -r requirements.txt Start app Go in the root dir and run these Streamlit str
Qimera: Data-free Quantization with Synthetic Boundary Supporting Samples
Qimera: Data-free Quantization with Synthetic Boundary Supporting Samples This repository is the official implementation of paper [Qimera: Data-free Q
YOLOv5 Series Multi-backbone, Pruning and quantization Compression Tool Box.
YOLOv5-Compression Update News Requirements 环境安装 pip install -r requirements.txt Evaluation metric Visdrone Model mAP mAP@50 Parameters(M) GFLOPs FPS@
Asterisk is a framework to generate high-quality training datasets at scale
Asterisk is a framework to generate high-quality training datasets at scale
[NeurIPS 2021] Better Safe Than Sorry: Preventing Delusive Adversaries with Adversarial Training
Better Safe Than Sorry: Preventing Delusive Adversaries with Adversarial Training Code for NeurIPS 2021 paper "Better Safe Than Sorry: Preventing Delu
code for generating data set ES-ImageNet with corresponding training code
es-imagenet-master code for generating data set ES-ImageNet with corresponding training code dataset generator some codes of ODG algorithm The variabl
A Context-aware Visual Attention-based training pipeline for Object Detection from a Webpage screenshot!
CoVA: Context-aware Visual Attention for Webpage Information Extraction Abstract Webpage information extraction (WIE) is an important step to create k
Code for the prototype tool in our paper "CoProtector: Protect Open-Source Code against Unauthorized Training Usage with Data Poisoning".
CoProtector Code for the prototype tool in our paper "CoProtector: Protect Open-Source Code against Unauthorized Training Usage with Data Poisoning".
Code for the prototype tool in our paper "CoProtector: Protect Open-Source Code against Unauthorized Training Usage with Data Poisoning".
CoProtector Code for the prototype tool in our paper "CoProtector: Protect Open-Source Code against Unauthorized Training Usage with Data Poisoning".
This is the official source code for SLATE. We provide the code for the model, the training code, and a dataset loader for the 3D Shapes dataset. This code is implemented in Pytorch.
SLATE This is the official source code for SLATE. We provide the code for the model, the training code and a dataset loader for the 3D Shapes dataset.
PyTorch Implementation of ByteDance's Cross-speaker Emotion Transfer Based on Speaker Condition Layer Normalization and Semi-Supervised Training in Text-To-Speech
Cross-Speaker-Emotion-Transfer - PyTorch Implementation PyTorch Implementation of ByteDance's Cross-speaker Emotion Transfer Based on Speaker Conditio
PyTorch Code for NeurIPS 2021 paper Anti-Backdoor Learning: Training Clean Models on Poisoned Data.
Anti-Backdoor Learning PyTorch Code for NeurIPS 2021 paper Anti-Backdoor Learning: Training Clean Models on Poisoned Data. Check the unlearning effect
Efficient Training of Visual Transformers with Small Datasets
Official codes for "Efficient Training of Visual Transformers with Small Datasets", NerIPS 2021.
Training Very Deep Neural Networks Without Skip-Connections
DiracNets v2 update (January 2018): The code was updated for DiracNets-v2 in which we removed NCReLU by adding per-channel a and b multipliers without
Training RNNs as Fast as CNNs
News SRU++, a new SRU variant, is released. [tech report] [blog] The experimental code and SRU++ implementation are available on the dev branch which
CVNets: A library for training computer vision networks
CVNets: A library for training computer vision networks This repository contains the source code for training computer vision models. Specifically, it
BERT model training impelmentation using 1024 A100 GPUs for MLPerf Training v1.1
Pre-trained checkpoint and bert config json file Location of checkpoint and bert config json file This MLCommons members Google Drive location contain
For auto aligning, cropping, and scaling HR and LR images for training image based neural networks
ImgAlign For auto aligning, cropping, and scaling HR and LR images for training image based neural networks Usage Make sure OpenCV is installed, 'pip
NAS-HPO-Bench-II is the first benchmark dataset for joint optimization of CNN and training HPs.
NAS-HPO-Bench-II API Overview NAS-HPO-Bench-II is the first benchmark dataset for joint optimization of CNN and training HPs. It helps a fair and low-
Improving Non-autoregressive Generation with Mixup Training
MIST Training MIST TRAIN_FILE=/your/path/to/train.json VALID_FILE=/your/path/to/valid.json OUTPUT_DIR=/your/path/to/save_checkpoints CACHE_DIR=/your/p
NeurIPS'21: Probabilistic Margins for Instance Reweighting in Adversarial Training (Pytorch implementation).
source code for NeurIPS21 paper robabilistic Margins for Instance Reweighting in Adversarial Training
Code release for "Cycle Self-Training for Domain Adaptation" (NeurIPS 2021)
CST Code release for "Cycle Self-Training for Domain Adaptation" (NeurIPS 2021) Prerequisites torch=1.7.0 torchvision qpsolvers numpy prettytable tqd
A library for preparing, training, and evaluating scalable deep learning hybrid recommender systems using PyTorch.
collie Collie is a library for preparing, training, and evaluating implicit deep learning hybrid recommender systems, named after the Border Collie do
QuakeLabeler is a Python package to create and manage your seismic training data, processes, and visualization in a single place — so you can focus on building the next big thing.
QuakeLabeler Quake Labeler was born from the need for seismologists and developers who are not AI specialists to easily, quickly, and independently bu
🔥🔥High-Performance Face Recognition Library on PaddlePaddle & PyTorch🔥🔥
face.evoLVe: High-Performance Face Recognition Library based on PaddlePaddle & PyTorch Evolve to be more comprehensive, effective and efficient for fa
The official code for PRIMER: Pyramid-based Masked Sentence Pre-training for Multi-document Summarization
PRIMER The official code for PRIMER: Pyramid-based Masked Sentence Pre-training for Multi-document Summarization. PRIMER is a pre-trained model for mu
Implements the training, testing and editing tools for "Pluralistic Image Completion"
Pluralistic Image Completion ArXiv | Project Page | Online Demo | Video(demo) This repository implements the training, testing and editing tools for "
A Deep Learning based project for creating line art portraits.
ArtLine The main aim of the project is to create amazing line art portraits. Sounds Intresting,let's get to the pictures!! Model-(Smooth) Model-(Quali
PyTorch image models, scripts, pretrained weights -- ResNet, ResNeXT, EfficientNet, EfficientNetV2, NFNet, Vision Transformer, MixNet, MobileNet-V3/V2, RegNet, DPN, CSPNet, and more
PyTorch Image Models Sponsors What's New Introduction Models Features Results Getting Started (Documentation) Train, Validation, Inference Scripts Awe
Synthetic structured data generators
Join us on What is Synthetic Data? Synthetic data is artificially generated data that is not collected from real world events. It replicates the stati
Source code for the paper "PLOME: Pre-training with Misspelled Knowledge for Chinese Spelling Correction" in ACL2021
PLOME:Pre-training with Misspelled Knowledge for Chinese Spelling Correction (ACL2021) This repository provides the code and data of the work in ACL20
PaSST: Efficient Training of Audio Transformers with Patchout
PaSST: Efficient Training of Audio Transformers with Patchout This is the implementation for Efficient Training of Audio Transformers with Patchout Pa
Vector Quantization, in Pytorch
Vector Quantization - Pytorch A vector quantization library originally transcribed from Deepmind's tensorflow implementation, made conveniently into a
Scalable training for dense retrieval models.
Scalable implementation of dense retrieval. Training on cluster By default it trains locally: PYTHONPATH=.:$PYTHONPATH python dpr_scale/main.py traine
NVIDIA Merlin is an open source library providing end-to-end GPU-accelerated recommender systems, from feature engineering and preprocessing to training deep learning models and running inference in production.
NVIDIA Merlin NVIDIA Merlin is an open source library designed to accelerate recommender systems on NVIDIA’s GPUs. It enables data scientists, machine
The official code for PRIMER: Pyramid-based Masked Sentence Pre-training for Multi-document Summarization
PRIMER The official code for PRIMER: Pyramid-based Masked Sentence Pre-training for Multi-document Summarization. PRIMER is a pre-trained model for mu
MG-GCN: Scalable Multi-GPU GCN Training Framework
MG-GCN MG-GCN: multi-GPU GCN training framework. For more information, please read our paper. After cloning our repository, run git submodule update -
Demystifying How Self-Supervised Features Improve Training from Noisy Labels
Demystifying How Self-Supervised Features Improve Training from Noisy Labels This code is a PyTorch implementation of the paper "[Demystifying How Sel
Multi-Task Pre-Training for Plug-and-Play Task-Oriented Dialogue System
Multi-Task Pre-Training for Plug-and-Play Task-Oriented Dialogue System Authors: Yixuan Su, Lei Shu, Elman Mansimov, Arshit Gupta, Deng Cai, Yi-An Lai
Codes for CIKM'21 paper 'Self-Supervised Graph Co-Training for Session-based Recommendation'.
COTREC Codes for CIKM'21 paper 'Self-Supervised Graph Co-Training for Session-based Recommendation'. Requirements: Python 3.7, Pytorch 1.6.0 Best Hype
Designing a Practical Degradation Model for Deep Blind Image Super-Resolution (ICCV, 2021) (PyTorch) - We released the training code!
Designing a Practical Degradation Model for Deep Blind Image Super-Resolution Kai Zhang, Jingyun Liang, Luc Van Gool, Radu Timofte Computer Vision Lab
Code associated with the paper "Towards Understanding the Data Dependency of Mixup-style Training".
Mixup-Data-Dependency Code associated with the paper "Towards Understanding the Data Dependency of Mixup-style Training". Running Alternating Line Exp
Anomaly detection in multi-agent trajectories: Code for training, evaluation and the OpenAI highway simulation.
Anomaly Detection in Multi-Agent Trajectories for Automated Driving This is the official project page including the paper, code, simulation, baseline
collect training and calibration data for gaze tracking
Collect Training and Calibration Data for Gaze Tracking This tool allows collecting gaze data necessary for personal calibration or training of eye-tr
Code for SALT: Stackelberg Adversarial Regularization, EMNLP 2021.
SALT: Stackelberg Adversarial Regularization Code for Adversarial Regularization as Stackelberg Game: An Unrolled Optimization Approach, EMNLP 2021. R
Multi-Task Pre-Training for Plug-and-Play Task-Oriented Dialogue System
Multi-Task Pre-Training for Plug-and-Play Task-Oriented Dialogue System Authors: Yixuan Su, Lei Shu, Elman Mansimov, Arshit Gupta, Deng Cai, Yi-An Lai
Propose a principled and practically effective framework for unsupervised accuracy estimation and error detection tasks with theoretical analysis and state-of-the-art performance.
Detecting Errors and Estimating Accuracy on Unlabeled Data with Self-training Ensembles This project is for the paper: Detecting Errors and Estimating
Spatial color quantization in Rust
rscolorq Rust port of Derrick Coetzee's scolorq, based on the 1998 paper "On spatial quantization of color images" by Jan Puzicha, Markus Held, Jens K
An Agnostic Computer Vision Framework - Pluggable to any Training Library: Fastai, Pytorch-Lightning with more to come
IceVision is the first agnostic computer vision framework to offer a curated collection with hundreds of high-quality pre-trained models from torchvision, MMLabs, and soon Pytorch Image Models. It orchestrates the end-to-end deep learning workflow allowing to train networks with easy-to-use robust high-performance libraries such as Pytorch-Lightning and Fastai
Shred your reddit comment and post history
trasheddit Shred your reddit comment and post history (x89/Shreddit replacement) Usage Simple Example Download trasheddit: git clone https://github.co
Composing methods for ML training efficiency
MosaicML Composer contains a library of methods, and ways to compose them together for more efficient ML training.
This is a library for training and applying sparse fine-tunings with torch and transformers.
This is a library for training and applying sparse fine-tunings with torch and transformers. Please refer to our paper Composable Sparse Fine-Tuning f
ECCV18 Workshops - Enhanced SRGAN. Champion PIRM Challenge on Perceptual Super-Resolution. The training codes are in BasicSR.
ESRGAN (Enhanced SRGAN) [ 🚀 BasicSR] [Real-ESRGAN] ✨ New Updates. We have extended ESRGAN to Real-ESRGAN, which is a more practical algorithm for rea
Cluster-GCN: An Efficient Algorithm for Training Deep and Large Graph Convolutional Networks
Cluster-GCN: An Efficient Algorithm for Training Deep and Large Graph Convolutional Networks This repository contains a TensorFlow implementation of "
PyTorch implementation of paper “Unbiased Scene Graph Generation from Biased Training”
A new codebase for popular Scene Graph Generation methods (2020). Visualization & Scene Graph Extraction on custom images/datasets are provided. It's also a PyTorch implementation of paper “Unbiased Scene Graph Generation from Biased Training CVPR 2020”