Python Efficient-training Resources

PseudoSeg: Designing Pseudo Labels for Semantic Segmentation PseudoSeg is a simple consistency training framework for semi-supervised image semantic s

Semi-Supervised Semantic Segmentation with Cross-Consistency Training (CCT) Paper, Project Page This repo contains the official implementation of CVPR

COResets and Data Subset selection Reduce end to end training time from days to hours (or hours to minutes), and energy requirements/costs by an order

Self-Training for Neural Sequence Generation This repo includes instructions for running noisy self-training algorithms from the following paper: Revi

MarginGAN This repository is the implementation of the paper "MarginGAN: Adversarial Training in Semi-Supervised Learning". 1."preliminary" is the imp

Neural Structured Learning in TensorFlow Neural Structured Learning (NSL) is a new learning paradigm to train neural networks by leveraging structured

Graph Contrastive Learning with Augmentations PyTorch implementation for Graph Contrastive Learning with Augmentations [poster] [appendix] Yuning You*

CCGL: Contrastive Cascade Graph Learning This repo provides a reference implementation of Contrastive Cascade Graph Learning (CCGL) framework as descr

opt-einsum-torch There have been many implementations of Einstein's summation. numpy's numpy.einsum is the least efficient one as it only runs in sing

A simplistic and efficient pure-python neural network library from Phys Whiz with CPU and GPU support.

In this project, two programs can help you take full agvantage of time on the model training with a remote server, which can push notification to your phone about the information during model training, like the model indices and unexpected interrupts. Then you can do something in time for your work.

recsys_metrics An efficient PyTorch implementation of the evaluation metrics in recommender systems. Overview • Installation • How to use • Benchmark

GCC: Graph Contrastive Coding for Graph Neural Network Pre-Training Original implementation for paper GCC: Graph Contrastive Coding for Graph Neural N

Expert-Linking Pytorch implementation of the paper "COAD: Contrastive Pre-training with Adversarial Fine-tuning for Zero-shot Expert Linking." This is

No-Transaction Band Network: A Neural Network Architecture for Efficient Deep Hedging Minimal implementation and experiments of "No-Transaction Band N

ElegantRL “小雅”: Scalable and Elastic Deep Reinforcement Learning ElegantRL is developed for researchers and practitioners with the following advantage

T-Zero This repository serves primarily as codebase and instructions for training, evaluation and inference of T0. T0 is the model developed in Multit

ALPRO Align and Prompt: Video-and-Language Pre-training with Entity Prompts [Paper] Dongxu Li, Junnan Li, Hongdong Li, Juan Carlos Niebles, Steven C.H

Pretrain-Recsys This is our Tensorflow implementation for our WSDM 2021 paper: Bowen Hao, Jing Zhang, Hongzhi Yin, Cuiping Li, Hong Chen. Pre-Training

G-Bert Pre-training of Graph Augmented Transformers for Medication Recommendation Intro G-Bert combined the power of Graph Neural Networks and BERT (B

GPT-GNN: Generative Pre-Training of Graph Neural Networks GPT-GNN is a pre-training framework to initialize GNNs by generative pre-training. It can be

Self-supervised edge features for improved Graph Neural Network training Data availability: Here is a link to the raw data for the organoids dataset.

DrRepair: Learning to Repair Programs from Error Messages This repo provides the source code & data of our paper: Graph-based, Self-Supervised Program

Autoregressive Predictive Coding This repository contains the official implementation (in PyTorch) of Autoregressive Predictive Coding (APC) proposed

Shuffle and Learn (Shuffle Tuple) Created by Ishan Misra Based on the ECCV 2016 Paper - "Shuffle and Learn: Unsupervised Learning using Temporal Order

CoCLR: Self-supervised Co-Training for Video Representation Learning This repository contains the implementation of: InfoNCE (MoCo on videos) UberNCE

There is More than Meets the Eye: Self-Supervised Multi-Object Detection and Tracking with Sound by Distilling Multimodal Knowledge MM-DistillNet is a

AdaFocusV2 This repo contains the official code and pre-trained models for AdaFo

Deep Learning Training Scripts DNN Frameworks Caffe PyTorch Tensorflow CNN Models VGG ResNet DenseNet Inception Language Modeling GatedCNN-LM Attentio

HiFi-GAN: Generative Adversarial Networks for Efficient and High Fidelity Speech Synthesis Jungil Kong, Jaehyeon Kim, Jaekyoung Bae In our paper, we p

This repository contains code of face emotion recognition that was developed in the RSF (Russian Science Foundation) project no. 20-71-10010 (Efficien

Memory-Efficient Multi-Level In-Situ Generation (MLG) By Jiaqi Gu, Hanqing Zhu, Chenghao Feng, Mingjie Liu, Zixuan Jiang, Ray T. Chen and David Z. Pan

Hub is a dataset format with a simple API for creating, storing, and collaborating on AI datasets of any size. The hub data layout enables rapid transformations and streaming of data while training models at scale. Hub is used by Google, Waymo, Red Cross, Oxford University, and Omdena.

This codebase is being actively maintained, please create and issue if you have issues using it Basics All data files are included under losses and ea

TUPE PyTorch implementation of Rethinking Positional Encoding in Language Pre-training. Quickstart Clone this repository. git clone https://github.com

SLIP: Self-supervision meets Language-Image Pre-training What you can find in this repo: Pre-trained models (with ViT-Small, Base, Large) and code to

A Unified Framework for Parameter-Efficient Transfer Learning This is the official implementation of the paper: Towards a Unified View of Parameter-Ef

Prompt-Tuning Implementation of "The Power of Scale for Parameter-Efficient Prompt Tuning" Currently, we support the following huggigface models: Bart

Sieve Video Data Collection Example Find samples that are interesting within hours of raw video, for free and completely automatically using Sieve API

DMT: Dynamic Mutual Training for Semi-Supervised Learning This repository contains the code for our paper DMT: Dynamic Mutual Training for Semi-Superv

Breaking the Curse of Space Explosion: Towards Effcient NAS with Curriculum Search Pytorch implementation for "Breaking the Curse of Space Explosion:

Introduction This is a Python package available on PyPI for NVIDIA-maintained utilities to streamline mixed precision and distributed training in Pyto

ONNX Runtime is a cross-platform inference and training machine-learning accelerator. ONNX Runtime inference can enable faster customer experiences an

Overview of Kubeflow Fairing Kubeflow Fairing is a Python package that streamlines the process of building, training, and deploying machine learning (

Global-Wheat-Detection An efficient PyTorch library for Global Wheat Detection using YOLOv5. The project is based on this Kaggle competition Global Wh

ConnectMP - Taking Multi-Process Data Sharing to the moon 🚀 Contribute · Community · Documentation 🎫 Introduction : 🍤 ConnectMP is the easiest and

SenFormer: Efficient Self-Ensemble Framework for Semantic Segmentation Efficient Self-Ensemble Framework for Semantic Segmentation by Walid Bousselham

MobileSal IEEE TPAMI 2021: MobileSal: Extremely Efficient RGB-D Salient Object Detection This repository contains full training & testing code, and pr

Data Efficient Language-Supervised Zero-Shot Recognition with Optimal Transport Distillation This repository contains PyTorch evaluation code, trainin

animeface deep models for anime images. Datasets anime-face-dataset Anime faces collected from Getchu.com. Based on Mckinsey666's dataset. 63.6K image

learned_optimization: Training and evaluating learned optimizers in JAX learned_optimization is a research codebase for training learned optimizers. I

HyperGBM Doc | 中文 We Are Hiring！ Dear folks,we are offering challenging opportunities located in Beijing for both professionals and students who are k

Recursive-NeRF: An Efficient and Dynamically Growing NeRF This is a Jittor implementation of Recursive-NeRF: An Efficient and Dynamically Growing NeRF

3D human pose estimation in video with temporal convolutions and semi-supervised training This is the implementation of the approach described in the

Opacus is a library that enables training PyTorch models with differential privacy. It supports training with minimal code changes required on the cli

Memory Efficient Attention This is unofficial implementation of Self-attention Does Not Need O(n^2) Memory for Jax and PyTorch. Implementation is almo

WORD: Revisiting Organs Segmentation in the Whole Abdominal Region (Paper and DataSet). [New] Note that all the emails about the download permission o

PokeGrinder 🤖 This is an Auto-Grinding bot made for Pokemeow. Efficient but not many features yet. Supported features This bot can currently handle :

Domain-informed Neural Networks Codes for building and training the neural network model described in Domain-informed neural networks for interaction

BLEND is a mechanism that can efficiently find fuzzy seed matches between sequences to significantly improve the performance and accuracy while reducing the memory space usage of two important applications: 1) finding overlapping reads and 2) read mapping. Described by Firtina et al.

PTvsBT On the Complementarity between Pre-Training and Back-Translation for Neural Machine Translation (Findings of EMNLP 2021) Citation Please cite a

Vision-aided GAN video (3m) | website | paper Can the collective knowledge from a large bank of pretrained vision models be leveraged to improve GAN t

Fine-grained Post-training for Multi-turn Response Selection Implements the model described in the following paper Fine-grained Post-training for Impr

Neural Volumes This repository contains training and evaluation code for the paper Neural Volumes. The method learns a 3D volumetric representation of

Data-Efficient GANs with DiffAugment project | paper | datasets | video | slides Generated using only 100 images of Obama, grumpy cats, pandas, the Br

SEW (Squeezed and Efficient Wav2vec) The repo contains the code of the paper "Performance-Efficiency Trade-offs in Unsupervised Pre-training for Speec

FastFormers FastFormers provides a set of recipes and methods to achieve highly efficient inference of Transformer models for Natural Language Underst

Sequential Transformer This is a code for training Transformers on sequential tasks such as language modeling. Unlike the original Transformer archite

PEGASUS library Pre-training with Extracted Gap-sentences for Abstractive SUmmarization Sequence-to-sequence models, or PEGASUS, uses self-supervised

Hiring We are hiring at all levels (including FTE researchers and interns)! If you are interested in working with us on NLP and large-scale pre-traine

FlauBERT and FLUE FlauBERT is a French BERT trained on a very large and heterogeneous French corpus. Models of different sizes are trained using the n

Introduction Funnel-Transformer is a new self-attention model that gradually compresses the sequence of hidden states to a shorter one and hence reduc

ProphetNet-X This repo provides the code for reproducing the experiments in ProphetNet. In the paper, we propose a new pre-trained language model call

ELECTRA Introduction ELECTRA is a method for self-supervised language representation learning. It can be used to pre-train transformer networks using

RangeLoss Pytorch This is a Pytorch reproduction of Range Loss, which is proposed in paper 《Range Loss for Deep Face Recognition with Long-Tailed Trai

Notice: Support for Python 3.6 will be dropped in v.0.2.1, please plan accordingly! Efficient and Scalable Physics-Informed Deep Learning Collocation-

Behavioural-Cloning-in-autonomous-driving Using CNN to mimic the driver based on training data from Torcs. Approach First, the data was collected from

Vit This is a simple program for training and testing vit. Key requirements: torch, torchvision and timm. Dataset I put 5 categories of the cub classi

Semi-Supervised Data Programming for Data Efficient Machine Learning SPEAR is a library for data programming with semi-supervision. The package implem

PantheonRL is a package for training and testing multi-agent reinforcement learning environments. PantheonRL supports cross-play, fine-tuning, ad-hoc coordination, and more.

HETU Documentation | Examples Hetu is a high-performance distributed deep learning system targeting trillions of parameters DL model training, develop

The pokemon showdown Python environment A Python interface to create battling pokemon agents. poke-env offers an easy-to-use interface for creating ru

PyGAD: Genetic Algorithm in Python PyGAD is an open-source easy-to-use Python 3 library for building the genetic algorithm and optimizing machine lear

Training Atari2600 by Reinforcement Learning Train Atari2600 and check how it works! How to Setup You can setup packages on your local env. $ make set

A lightweight library designed to accelerate the process of training PyTorch models by providing a minimal, but extensible training loop which is flexible enough to handle the majority of use cases, and capable of utilizing different hardware options with no code changes required.

Programmatically Build and Manage Training Data Announcement The Snorkel team is now focusing their efforts on Snorkel Flow, an end-to-end AI applicat

Region_Learner The Pytorch implementation for "Video-Text Pre-training with Learned Regions" (arxiv) We are still cleaning up the code further and pre

MMGEN-FaceStylor English | 简体中文 Introduction This repo is an efficient toolkit for Face Stylization based on the paper "AgileGAN: Stylizing Portraits

Maximum Likelihood Training of Score-Based Diffusion Models This repo contains the official implementation for the paper Maximum Likelihood Training o

rastrainer rastrainer is a QGIS plugin to training remote sensing semantic segmentation model based on PaddlePaddle. UI TODO Init UI. Add Block. Add l

Unimodal Face Classification with Multimodal Training This is a PyTorch implementation of the following paper: Unimodal Face Classification with Multi

Official Implementation of SimIPU SimIPU: Simple 2D Image and 3D Point Cloud Unsupervised Pre-Training for Spatial-Aware Visual Representations Since

IterMVS official source code of paper 'IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo' Introduction IterMVS is a novel lear

    VarCLR: Variable Representation Pre-training via Contrastive Learning New: Paper accepted by ICSE 2022. Preprint at arXiv! This repository contain

Image BERT Pre-Training with iBOT Official PyTorch implementation and pretrained models for paper iBOT: Image BERT Pre-Training with Online Tokenizer.

Unequal-Training-for-Deep-Face-Recognition-with-Long-Tailed-Noisy-Data. This is the code of CVPR 2019 paper《Unequal Training for Deep Face Recognition

Conceptual 12M We introduce the Conceptual 12M (CC12M), a dataset with ~12 million image-text pairs meant to be used for vision-and-language pre-train

CReST in Tensorflow 2 Code for the paper: "CReST: A Class-Rebalancing Self-Training Framework for Imbalanced Semi-Supervised Learning" by Chen Wei, Ki

Uni-Fold: Training your own deep protein-folding models. This package provides and implementation of a trainable, Transformer-based deep protein foldi

Recipes are a standard, well supported set of blueprints for machine learning engineers to rapidly train models using the latest research techniques without significant engineering overhead.Specifically, recipes aims to provide- Consistent access to pre-trained SOTA models ready for production- Reference implementations for SOTA research reproducibility, and infrastructure to guarantee correctness, efficiency, and interoperability.