1017 Repositories
Python normalization-free-training Libraries
VideoMAE: Masked Autoencoders are Data-Efficient Learners for Self-Supervised Video Pre-Training
Masked Autoencoders are Data-Efficient Learners for Self-Supervised Video Pre-Training [Arxiv] VideoMAE: Masked Autoencoders are Data-Efficient Learne
Official code for our CVPR '22 paper "Dataset Distillation by Matching Training Trajectories"
Dataset Distillation by Matching Training Trajectories Project Page | Paper This repo contains code for training expert trajectories and distilling sy
ViewFormer: NeRF-free Neural Rendering from Few Images Using Transformers
ViewFormer: NeRF-free Neural Rendering from Few Images Using Transformers Official implementation of ViewFormer. ViewFormer is a NeRF-free neural rend
"SinNeRF: Training Neural Radiance Fields on Complex Scenes from a Single Image", Dejia Xu, Yifan Jiang, Peihao Wang, Zhiwen Fan, Humphrey Shi, Zhangyang Wang
SinNeRF: Training Neural Radiance Fields on Complex Scenes from a Single Image [Paper] [Website] Pipeline Code Environment pip install -r requirements
✨ Real-life Data Analysis and Model Training Workshop by Global AI Hub.
🎓 Data Analysis and Model Training Course by Global AI Hub Syllabus: Day 1 What is Data? Multimedia Structured and Unstructured Data Data Types Data
FCOSR: A Simple Anchor-free Rotated Detector for Aerial Object Detection
FCOSR: A Simple Anchor-free Rotated Detector for Aerial Object Detection FCOSR: A Simple Anchor-free Rotated Detector for Aerial Object Detection arXi
[CVPR 2022 Oral] Versatile Multi-Modal Pre-Training for Human-Centric Perception
Versatile Multi-Modal Pre-Training for Human-Centric Perception Fangzhou Hong1 Liang Pan1 Zhongang Cai1,2,3 Ziwei Liu1* 1S-Lab, Nanyang Technologic
CLOOB training (JAX) and inference (JAX and PyTorch)
cloob-training Pretrained models There are two pretrained CLOOB models in this repo at the moment, a 16 epoch and a 32 epoch ViT-B/16 checkpoint train
Free Data Engineering course!
Data Engineering Zoomcamp Register in DataTalks.Club's Slack Join the #course-data-engineering channel The videos are published to DataTalks.Club's Yo
Free MLOps course from DataTalks.Club
MLOps Zoomcamp Our MLOps Zoomcamp course Sign up here: https://airtable.com/shrCb8y6eTbPKwSTL (it's not automated, you will not receive an email immed
This repository contains the best Data Science free hand-picked resources to equip you with all the industry-driven skills and interview preparation kit.
Best Data Science Resources Hey, Data Enthusiasts out there! Finally, after lots of requests from the community I finally came up with the best free D
Example notebooks for working with SageMaker Studio Lab. Sign up for an account at the link below!
SageMaker Studio Lab Sample Notebooks Available today in public preview. If you are looking for a no-cost compute environment to run Jupyter notebooks
All of the figures and notebooks for my deep learning book, for free!
"Deep Learning - A Visual Approach" by Andrew Glassner This is the official repo for my book from No Starch Press. Ordering the book My book is called
MetaShift: A Dataset of Datasets for Evaluating Contextual Distribution Shifts and Training Conflicts (ICLR 2022)
MetaShift: A Dataset of Datasets for Evaluating Distribution Shifts and Training Conflicts This repo provides the PyTorch source code of our paper: Me
BigDetection: A Large-scale Benchmark for Improved Object Detector Pre-training
BigDetection: A Large-scale Benchmark for Improved Object Detector Pre-training By Likun Cai, Zhi Zhang, Yi Zhu, Li Zhang, Mu Li, Xiangyang Xue. This
Georeferencing large amounts of data for free.
Geolocate Georeferencing large amounts of data for free. Special thanks to @brunodepauloalmeida and the whole team for the contributions. How? It's us
gget is a free and open-source command-line tool and Python package that enables efficient querying of genomic databases.
gget is a free and open-source command-line tool and Python package that enables efficient querying of genomic databases. gget consists of a collection of separate but interoperable modules, each designed to facilitate one type of database querying in a single line of code.
Coreference resolution for English, French, German and Polish, optimised for limited training data and easily extensible for further languages
Coreferee Author: Richard Paul Hudson, Explosion AI 1. Introduction 1.1 The basic idea 1.2 Getting started 1.2.1 English 1.2.2 French 1.2.3 German 1.2
Official PyTorch implementation of "RMGN: A Regional Mask Guided Network for Parser-free Virtual Try-on" (IJCAI-ECAI 2022)
RMGN-VITON RMGN: A Regional Mask Guided Network for Parser-free Virtual Try-on In IJCAI-ECAI 2022(short oral). [Paper] [Supplementary Material] Abstra
This is a free python bot program that crosses you to farm with auto click in space crypto NFT game, having fun :) Creator: Marlon Zanardi
🚀 Space Crypto auto click bot ready-to-use 🚀 This is a free python bot program that crosses you to farm with auto click in space crypto NFT game, ha
Repository for training material for the 2022 SDSC HPC/CI User Training Course
hpc-training-2022 Repository for training material for the 2022 SDSC HPC/CI Training Series HPC/CI Training Series home https://www.sdsc.edu/event_ite
Easy Parallel Library (EPL) is a general and efficient deep learning framework for distributed model training.
English | 简体中文 Easy Parallel Library Overview Easy Parallel Library (EPL) is a general and efficient library for distributed model training. Usability
code for TCL: Vision-Language Pre-Training with Triple Contrastive Learning, CVPR 2022
Vision-Language Pre-Training with Triple Contrastive Learning, CVPR 2022 News (03/16/2022) upload retrieval checkpoints finetuned on COCO and Flickr T
A free sniper bot built to work with PancakeSwap: Router V2
Pancakeswap Sniper Bot PancakeSwap sniper bot. Automated sniping bot to snipe crypto coin launches. How it works The sniping bot can be used in three
An introduction to free, automated web scraping with GitHub’s powerful new Actions framework.
An introduction to free, automated web scraping with GitHub’s powerful new Actions framework Published at palewi.re/docs/first-github-scraper/ Contrib
torchlm is aims to build a high level pipeline for face landmarks detection, it supports training, evaluating, exporting, inference(Python/C++) and 100+ data augmentations
💎A high level pipeline for face landmarks detection, supports training, evaluating, exporting, inference and 100+ data augmentations, compatible with torchvision and albumentations, can easily install with pip.
Bot developed in python, 100% open-source, compatible with Windows and Linux.
Bombcrypto Bot [Family JOW] Bot desenvolvido em python, 100% do código é aberto, para aqueles que tenham conhecimento validarem que não existe nenhum
MarcoPolo is a clustering-free approach to the exploration of bimodally expressed genes along with group information in single-cell RNA-seq data
MarcoPolo is a method to discover differentially expressed genes in single-cell RNA-seq data without depending on prior clustering Overview MarcoPolo
Azure free vpn for students only! (Self hosted/No sketchy services/Fast and free)
Azpn-Azure-Free-VPN Azure free vpn for students only! (Self hosted/No sketchy services/Fast and free) This is an alternative secure way of accessing f
As-ViT: Auto-scaling Vision Transformers without Training
As-ViT: Auto-scaling Vision Transformers without Training [PDF] Wuyang Chen, Wei Huang, Xianzhi Du, Xiaodan Song, Zhangyang Wang, Denny Zhou In ICLR 2
Free course that takes you from zero to Reinforcement Learning PRO 🦸🏻🦸🏽
The Hands-on Reinforcement Learning course 🚀 From zero to HERO 🦸🏻🦸🏽 Out of intense complexities, intense simplicities emerge. -- Winston Churchi
CLIP (Contrastive Language–Image Pre-training) for Italian
Italian CLIP CLIP (Radford et al., 2021) is a multimodal model that can learn to represent images and text jointly in the same space. In this project,
🏎️ Accelerate training and inference of 🤗 Transformers with easy to use hardware optimization tools
Hugging Face Optimum 🤗 Optimum is an extension of 🤗 Transformers, providing a set of performance optimization tools enabling maximum efficiency to t
Official repository of OFA. Paper: Unifying Architectures, Tasks, and Modalities Through a Simple Sequence-to-Sequence Learning Framework
Paper | Blog OFA is a unified multimodal pretrained model that unifies modalities (i.e., cross-modality, vision, language) and tasks (e.g., image gene
A repository to run gpt-j-6b on low vram machines (4.2 gb minimum vram for 2000 token context, 3.5 gb for 1000 token context). Model loading takes 12gb free ram.
Basic-UI-for-GPT-J-6B-with-low-vram A repository to run GPT-J-6B on low vram systems by using both ram, vram and pinned memory. There seem to be some
Code of paper: "DropAttack: A Masked Weight Adversarial Training Method to Improve Generalization of Neural Networks"
DropAttack: A Masked Weight Adversarial Training Method to Improve Generalization of Neural Networks Abstract: Adversarial training has been proven to
Potato Disease Classification - Training, Rest APIs, and Frontend to test.
Potato Disease Classification Setup for Python: Install Python (Setup instructions) Install Python packages pip3 install -r training/requirements.txt
🍷 Gracefully claim weekly free games and monthly content from Epic Store.
EPIC 免费人 🚀 优雅地领取 Epic 免费游戏 Introduction 👋 Epic AwesomeGamer 帮助玩家优雅地领取 Epic 免费游戏。 使用 「Epic免费人」可以实现如下需求: get:搬空游戏商店,获取所有常驻免费游戏与免费附加内容; claim:领取周免游戏及其免
TorchMultimodal is a PyTorch library for training state-of-the-art multimodal multi-task models at scale.
TorchMultimodal (Alpha Release) Introduction TorchMultimodal is a PyTorch library for training state-of-the-art multimodal multi-task models at scale.
PromptDet: Expand Your Detector Vocabulary with Uncurated Images
PromptDet: Expand Your Detector Vocabulary with Uncurated Images Paper Website Introduction The goal of this work is to establish a scalable pipeline
Code for our paper "Graph Pre-training for AMR Parsing and Generation" in ACL2022
AMRBART An implementation for ACL2022 paper "Graph Pre-training for AMR Parsing and Generation". You may find our paper here (Arxiv). Requirements pyt
[ICLR 2022] Pretraining Text Encoders with Adversarial Mixture of Training Signal Generators
AMOS This repository contains the scripts for fine-tuning AMOS pretrained models on GLUE and SQuAD 2.0 benchmarks. Paper: Pretraining Text Encoders wi
Commonality in Natural Images Rescues GANs: Pretraining GANs with Generic and Privacy-free Synthetic Data - Official PyTorch Implementation (CVPR 2022)
Commonality in Natural Images Rescues GANs: Pretraining GANs with Generic and Privacy-free Synthetic Data (CVPR 2022) Potentials of primitive shapes f
Beyond Masking: Demystifying Token-Based Pre-Training for Vision Transformers
beyond masking Beyond Masking: Demystifying Token-Based Pre-Training for Vision Transformers The code is coming Figure 1: Pipeline of token-based pre-
Large-Scale Pre-training for Person Re-identification with Noisy Labels (LUPerson-NL)
LUPerson-NL Large-Scale Pre-training for Person Re-identification with Noisy Labels (LUPerson-NL) The repository is for our CVPR2022 paper Large-Scale
This is a Python bot, which automates logging in, purchasing and planting the seeds. Open source bot and completely free.
🌻 Sunflower Land Bot 🌻 ⚠️ Warning I am not responsible for any penalties incurred by those who use the bot, use it at your own risk. This BOT is com
SIGIR'22 paper: Axiomatically Regularized Pre-training for Ad hoc Search
Introduction This codebase contains source-code of the Python-based implementation (ARES) of our SIGIR 2022 paper. Chen, Jia, et al. "Axiomatically Re
CLIP-GEN: Language-Free Training of a Text-to-Image Generator with CLIP
CLIP-GEN [简体中文][English] 本项目在萤火二号集群上用 PyTorch 实现了论文 《CLIP-GEN: Language-Free Training of a Text-to-Image Generator with CLIP》。 CLIP-GEN 是一个 Language-F
Multi Brute Force Facebook - Crack Facebook With Login - Free For Now
✭ SAKERA CRACK Made With ❤️ By Denventa, Araya, Dapunta Author: - Denventa - Araya Dev - Dapunta Khurayra X ⇨ Fitur Login [✯] Login Cookies ⇨ Ins
DeepGNN is a framework for training machine learning models on large scale graph data.
DeepGNN Overview DeepGNN is a framework for training machine learning models on large scale graph data. DeepGNN contains all the necessary features in
Aiming at the common training datsets split, spectrum preprocessing, wavelength select and calibration models algorithm involved in the spectral analysis process
Aiming at the common training datsets split, spectrum preprocessing, wavelength select and calibration models algorithm involved in the spectral analysis process, a complete algorithm library is established, which is named opensa (openspectrum analysis).
Princeton NLP's pre-training library based on fairseq with DeepSpeed kernel integration 🚃
This repository provides a library for efficient training of masked language models (MLM), built with fairseq. We fork fairseq to give researchers mor
This library is helpful when creating accounts, it has everything you need for this
AccountGeneratorHelper Library to facilitate accounts generation. Unofficial API for temp email services. Receive SMS from free services. Parsing and
Code for our SIGIR 2022 accepted paper : P3 Ranker: Mitigating the Gaps between Pre-training and Ranking Fine-tuning with Prompt-based Learning and Pre-finetuning
P3 Ranker Implementation for our SIGIR2022 accepted paper: P3 Ranker: Mitigating the Gaps between Pre-training and Ranking Fine-tuning with Prompt-bas
Text classification is one of the popular tasks in NLP that allows a program to classify free-text documents based on pre-defined classes.
Deep-Learning-for-Text-Document-Classification Text classification is one of the popular tasks in NLP that allows a program to classify free-text docu
In this project we predict the forest cover type using the cartographic variables in the training/test datasets.
Kaggle Competition: Forest Cover Type Prediction In this project we predict the forest cover type (the predominant kind of tree cover) using the carto
Implementaion of our ACL 2022 paper Bridging the Data Gap between Training and Inference for Unsupervised Neural Machine Translation
Bridging the Data Gap between Training and Inference for Unsupervised Neural Machine Translation This is the implementaion of our paper: Bridging the
Source files for a free pyRevit toolbar.
pyRoovit (WIP) What is this? PyRoovit is/will be a toolbar for the use with pyRevit built by Gavin Crump (aka Aussie BIM Guru). Having used and taught
Repository for DNN training, theory to practice, part of the Large Scale Machine Learning class at Mines Paritech
DNN Training, from theory to practice This repository is complementary to the deep learning training lesson given to les Mines ParisTech on the 11th o
[CVPR 2022] "The Principle of Diversity: Training Stronger Vision Transformers Calls for Reducing All Levels of Redundancy" by Tianlong Chen, Zhenyu Zhang, Yu Cheng, Ahmed Awadallah, Zhangyang Wang
The Principle of Diversity: Training Stronger Vision Transformers Calls for Reducing All Levels of Redundancy Codes for this paper: [CVPR 2022] The Pr
Architecture Patterns with Python (TDD, DDD, EDM)
architecture-traning Architecture Patterns with Python (TDD, DDD, EDM) Chapter 5. 높은 기어비와 낮은 기어비의 TDD 5.2 도메인 계층 테스트를 서비스 계층으로 옮겨야 하는가? 도메인 계층 테스트 def
Codes for "Template-free Prompt Tuning for Few-shot NER".
EntLM The source codes for EntLM. Dependencies: Cuda 10.1, python 3.6.5 To install the required packages by following commands: $ pip3 install -r requ
E2e music remastering system - End-to-end Music Remastering System Using Self-supervised and Adversarial Training
End-to-end Music Remastering System This repository includes source code and pre
Roblox-Account-Gen - A simple account generator not using paid solving services
Roblox Account Generator Star this if it helped to spread awareness! No 2captcha
Super-Fast-Adversarial-Training - A PyTorch Implementation code for developing super fast adversarial training
Super-Fast-Adversarial-Training This is a PyTorch Implementation code for develo
Http-proxy-list - A lightweight project that hourly scrapes lots of free-proxy sites, validates if it works, and serves a clean proxy list
Free HTTP Proxy List 🌍 It is a lightweight project that hourly scrapes lots of
Sphinx-performance - CLI tool to measure the build time of different, free configurable Sphinx-Projects
CLI tool to measure the build time of different, free configurable Sphinx-Projec
HashNeRF-pytorch - Pure PyTorch Implementation of NVIDIA paper on Instant Training of Neural Graphics primitives
HashNeRF-pytorch Instant-NGP recently introduced a Multi-resolution Hash Encodin
Gba-free-fonts - Free font resources for GBA game development
gba-free-fonts Free font resources for GBA game development This repo contains m
Unifying Architectures, Tasks, and Modalities Through a Simple Sequence-to-Sequence Learning Framework
Official repository of OFA. Paper: Unifying Architectures, Tasks, and Modalities Through a Simple Sequence-to-Sequence Learning Framework
Download nitro generator that generates free nitro code that you can use for Discord
Download nitro generator that generates free nitro code that you can use for Discord, run it and wait for free nitro to come
An Advance Discord Generator Written in python Verified Email and Phone Number For Free!
Intro An Advance Discord Generator Written in python It can generate nearly fully verified tokens USAGE put server invite code inside ( invitecode = "
Learning Features with Parameter-Free Layers, ICLR 2022
Learning Features with Parameter-Free Layers (ICLR 2022) Dongyoon Han, YoungJoon Yoo, Beomyoung Kim, Byeongho Heo | Paper NAVER AI Lab, NAVER CLOVA Up
The Unreasonable Effectiveness of Random Pruning: Return of the Most Naive Baseline for Sparse Training
[ICLR 2022] The Unreasonable Effectiveness of Random Pruning: Return of the Most Naive Baseline for Sparse Training The Unreasonable Effectiveness of
LyaNet: A Lyapunov Framework for Training Neural ODEs
LyaNet: A Lyapunov Framework for Training Neural ODEs Provide the model type--config-name to train and test models configured as those shown in the pa
This is the replication package for paper submission: Towards Training Reproducible Deep Learning Models.
This is the replication package for paper submission: Towards Training Reproducible Deep Learning Models.
OpenARB is an open source program aiming to emulate a free market while encouraging players to participate in arbitrage in order to increase working capital.
Overview OpenARB is an open source program aiming to emulate a free market while encouraging players to participate in arbitrage in order to increase
JFB: Jacobian-Free Backpropagation for Implicit Models
JFB: Jacobian-Free Backpropagation for Implicit Models
Monocular 3D Object Detection: An Extrinsic Parameter Free Approach (CVPR2021)
Monocular 3D Object Detection: An Extrinsic Parameter Free Approach (CVPR2021) Yunsong Zhou, Yuan He, Hongzi Zhu, Cheng Wang, Hongyang Li, Qinhong Jia
Learning Features with Parameter-Free Layers (ICLR 2022)
Learning Features with Parameter-Free Layers (ICLR 2022) Dongyoon Han, YoungJoon Yoo, Beomyoung Kim, Byeongho Heo | Paper NAVER AI Lab, NAVER CLOVA Up
To build a regression model to predict the concrete compressive strength based on the different features in the training data.
Cement-Strength-Prediction Problem Statement To build a regression model to predict the concrete compressive strength based on the different features
A training task for web scraping using python multithreading and a real-time-updated list of available proxy servers.
Parallel web scraping The project is a training task for web scraping using python multithreading and a real-time-updated list of available proxy serv
Official code of Retinal Vessel Segmentation with Pixel-wise Adaptive Filters and Consistency Training
Official code of Retinal Vessel Segmentation with Pixel-wise Adaptive Filters and Consistency Training (ISBI 2022)
PyTorch implementation of the ExORL: Exploratory Data for Offline Reinforcement Learning
ExORL: Exploratory Data for Offline Reinforcement Learning This is an original PyTorch implementation of the ExORL framework from Don't Change the Alg
The source code for Generating Training Data with Language Models: Towards Zero-Shot Language Understanding.
SuperGen The source code for Generating Training Data with Language Models: Towards Zero-Shot Language Understanding. Requirements Before running, you
Implementations of the algorithms in the paper Approximative Algorithms for Multi-Marginal Optimal Transport and Free-Support Wasserstein Barycenters
Implementations of the algorithms in the paper Approximative Algorithms for Multi-Marginal Optimal Transport and Free-Support Wasserstein Barycenters
FewBit — a library for memory efficient training of large neural networks
FewBit FewBit — a library for memory efficient training of large neural networks. Its efficiency originates from storage optimizations applied to back
Code for the tech report Toward Training at ImageNet Scale with Differential Privacy
Differentially private Imagenet training Code for the tech report Toward Training at ImageNet Scale with Differential Privacy by Alexey Kurakin, Steve
Official PyTorch implementation of the paper "Likelihood Training of Schrödinger Bridge using Forward-Backward SDEs Theory (SB-FBSDE)"
Official PyTorch implementation of the paper "Likelihood Training of Schrödinger Bridge using Forward-Backward SDEs Theory (SB-FBSDE)" which introduces a new class of deep generative models that generalizes score-based models to fully nonlinear forward and backward diffusions.
This repository provides an efficient PyTorch-based library for training deep models.
An Efficient Library for Training Deep Models This repository provides an efficient PyTorch-based library for training deep models. Installation Make
Text Normalization(文本正则化)
Text Normalization(文本正则化) 任务描述:通过机器学习算法将英文文本的“手写”形式转换成“口语“形式,例如“6ft”转换成“six feet”等 实验结果 XGBoost + bag-of-words: 0.99159 XGBoost+Weights+rules:0.99002
Free TradingView webhook alert for basic plan users.
TradingView-Free-Webhook-Alerts Project start on 01-02-2022 Providing the free webhook service to the basic plan users in TradingView. Portal ↠ Instal
Human segmentation models, training/inference code, and trained weights, implemented in PyTorch
Human-Segmentation-PyTorch Human segmentation models, training/inference code, and trained weights, implemented in PyTorch. Supported networks UNet: b
Pytorch implementation of the paper "Enhancing Content Preservation in Text Style Transfer Using Reverse Attention and Conditional Layer Normalization"
Pytorch implementation of the paper "Enhancing Content Preservation in Text Style Transfer Using Reverse Attention and Conditional Layer Normalization"
Data from "Datamodels: Predicting Predictions with Training Data"
Data from "Datamodels: Predicting Predictions with Training Data" Here we provid
Training a deep learning model on the noisy CIFAR dataset
Training-a-deep-learning-model-on-the-noisy-CIFAR-dataset This repository contai
Simple codebase for flexible neural net training
neural-modular Simple codebase for flexible neural net training. Allows for seamless exchange of models, dataset, and optimizers. Uses hydra for confi
This is an early in-development version of training CLIP models with hivemind.
A transformer that does not hog your GPU memory This is an early in-development codebase: if you want a stable and documented hivemind codebase, look
The NewSHead dataset is a multi-doc headline dataset used in NHNet for training a headline summarization model.
This repository contains the raw dataset used in NHNet [1] for the task of News Story Headline Generation. The code of data processing and training is available under Tensorflow Models - NHNet.
PyTorch code for BLIP: Bootstrapping Language-Image Pre-training for Unified Vision-Language Understanding and Generation
BLIP: Bootstrapping Language-Image Pre-training for Unified Vision-Language Understanding and Generation