1357 Repositories
Python self-critical-sequence-training Libraries
changedetection.io - The best and simplest self-hosted website change detection monitoring service
changedetection.io - The best and simplest self-hosted website change detection monitoring service. An alternative to Visualping, Watchtower etc. Designed for simplicity - the main goal is to simply monitor which websites had a text change. Open source web page change detection.
Sandwich Batch Normalization
Sandwich Batch Normalization Code for Sandwich Batch Normalization. Introduction We present Sandwich Batch Normalization (SaBN), an extremely easy imp
Implementation of SETR model, Original paper: Rethinking Semantic Segmentation from a Sequence-to-Sequence Perspective with Transformers.
SETR - Pytorch Since the original paper (Rethinking Semantic Segmentation from a Sequence-to-Sequence Perspective with Transformers.) has no official
Simple tutorials on Pytorch DDP training
pytorch-distributed-training Distribute Dataparallel (DDP) Training on Pytorch Features Easy to study DDP training You can directly copy this code for
Implementation of Nyström Self-attention, from the paper Nyströmformer
Nyström Attention Implementation of Nyström Self-attention, from the paper Nyströmformer. Yannic Kilcher video Install $ pip install nystrom-attention
Unsupervised Semantic Segmentation by Contrasting Object Mask Proposals.
Unsupervised Semantic Segmentation by Contrasting Object Mask Proposals This repo contains the Pytorch implementation of our paper: Unsupervised Seman
Free and Open Source Machine Translation API. 100% self-hosted, no limits, no ties to proprietary services. Built on top of Argos Translate.
LibreTranslate Try it online! | API Docs Free and Open Source Machine Translation API, entirely self-hosted. Unlike other APIs, it doesn't rely on pro
Learning to Initialize Neural Networks for Stable and Efficient Training
GradInit This repository hosts the code for experiments in the paper, GradInit: Learning to Initialize Neural Networks for Stable and Efficient Traini
Reviving Iterative Training with Mask Guidance for Interactive Segmentation
This repository provides the source code for training and testing state-of-the-art click-based interactive segmentation models with the official PyTorch implementation
Implementation of self-attention mechanisms for general purpose. Focused on computer vision modules. Ongoing repository.
Self-attention building blocks for computer vision applications in PyTorch Implementation of self attention mechanisms for computer vision in PyTorch
Bidirectional LSTM-CRF and ELMo for Named-Entity Recognition, Part-of-Speech Tagging and so on.
anaGo anaGo is a Python library for sequence labeling(NER, PoS Tagging,...), implemented in Keras. anaGo can solve sequence labeling tasks such as nam
🏖 Easy training and deployment of seq2seq models.
Headliner Headliner is a sequence modeling library that eases the training and in particular, the deployment of custom sequence models for both resear
Kashgari is a production-level NLP Transfer learning framework built on top of tf.keras for text-labeling and text-classification, includes Word2Vec, BERT, and GPT2 Language Embedding.
Kashgari Overview | Performance | Installation | Documentation | Contributing 🎉 🎉 🎉 We released the 2.0.0 version with TF2 Support. 🎉 🎉 🎉 If you
Sequence-to-sequence framework with a focus on Neural Machine Translation based on Apache MXNet
Sockeye This package contains the Sockeye project, an open-source sequence-to-sequence framework for Neural Machine Translation based on Apache MXNet
DELTA is a deep learning based natural language and speech processing platform.
DELTA - A DEep learning Language Technology plAtform What is DELTA? DELTA is a deep learning based end-to-end natural language and speech processing p
A framework for training and evaluating AI models on a variety of openly available dialogue datasets.
ParlAI (pronounced “par-lay”) is a python framework for sharing, training and testing dialogue models, from open-domain chitchat, to task-oriented dia
A very simple framework for state-of-the-art Natural Language Processing (NLP)
A very simple framework for state-of-the-art NLP. Developed by Humboldt University of Berlin and friends. IMPORTANT: (30.08.2020) We moved our models
Facebook AI Research Sequence-to-Sequence Toolkit written in Python.
Fairseq(-py) is a sequence modeling toolkit that allows researchers and developers to train custom models for translation, summarization, language mod
Authors implementation of LieTransformer: Equivariant Self-Attention for Lie Groups
LieTransformer This repository contains the implementation of the LieTransformer used for experiments in the paper LieTransformer: Equivariant self-at
This is a Pytorch implementation of the paper: Self-Supervised Graph Transformer on Large-Scale Molecular Data.
This is a Pytorch implementation of the paper: Self-Supervised Graph Transformer on Large-Scale Molecular Data.
Checkout some cool self-projects you can try your hands on to curb your boredom this December!
SoC-Winter Checkout some cool self-projects you can try your hands on to curb your boredom this December! These are short projects that you can do you
CFC-Net: A Critical Feature Capturing Network for Arbitrary-Oriented Object Detection in Remote Sensing Images
CFC-Net This project hosts the official implementation for the paper: CFC-Net: A Critical Feature Capturing Network for Arbitrary-Oriented Object Dete
GAP-text2SQL: Learning Contextual Representations for Semantic Parsing with Generation-Augmented Pre-Training
GAP-text2SQL: Learning Contextual Representations for Semantic Parsing with Generation-Augmented Pre-Training Code and model from our AAAI 2021 paper
Bidirectional LSTM-CRF and ELMo for Named-Entity Recognition, Part-of-Speech Tagging and so on.
anaGo anaGo is a Python library for sequence labeling(NER, PoS Tagging,...), implemented in Keras. anaGo can solve sequence labeling tasks such as nam
🏖 Easy training and deployment of seq2seq models.
Headliner Headliner is a sequence modeling library that eases the training and in particular, the deployment of custom sequence models for both resear
Kashgari is a production-level NLP Transfer learning framework built on top of tf.keras for text-labeling and text-classification, includes Word2Vec, BERT, and GPT2 Language Embedding.
Kashgari Overview | Performance | Installation | Documentation | Contributing 🎉 🎉 🎉 We released the 2.0.0 version with TF2 Support. 🎉 🎉 🎉 If you
Sequence-to-sequence framework with a focus on Neural Machine Translation based on Apache MXNet
Sockeye This package contains the Sockeye project, an open-source sequence-to-sequence framework for Neural Machine Translation based on Apache MXNet
DELTA is a deep learning based natural language and speech processing platform.
DELTA - A DEep learning Language Technology plAtform What is DELTA? DELTA is a deep learning based end-to-end natural language and speech processing p
A framework for training and evaluating AI models on a variety of openly available dialogue datasets.
ParlAI (pronounced “par-lay”) is a python framework for sharing, training and testing dialogue models, from open-domain chitchat, to task-oriented dia
A very simple framework for state-of-the-art Natural Language Processing (NLP)
A very simple framework for state-of-the-art NLP. Developed by Humboldt University of Berlin and friends. IMPORTANT: (30.08.2020) We moved our models
Facebook AI Research Sequence-to-Sequence Toolkit written in Python.
Fairseq(-py) is a sequence modeling toolkit that allows researchers and developers to train custom models for translation, summarization, language mod
Fast and Easy Infinite Neural Networks in Python
Neural Tangents ICLR 2020 Video | Paper | Quickstart | Install guide | Reference docs | Release notes Overview Neural Tangents is a high-level neural
High-level library to help with training and evaluating neural networks in PyTorch flexibly and transparently.
TL;DR Ignite is a high-level library to help with training and evaluating neural networks in PyTorch flexibly and transparently. Click on the image to
A Neural Net Training Interface on TensorFlow, with focus on speed + flexibility
Tensorpack is a neural network training interface based on TensorFlow. Features: It's Yet Another TF high-level API, with speed, and flexibility built
PArallel Distributed Deep LEarning: Machine Learning Framework from Industrial Practice (『飞桨』核心框架,深度学习&机器学习高性能单机、分布式训练和跨平台部署)
English | 简体中文 Welcome to the PaddlePaddle GitHub. PaddlePaddle, as the only independent R&D deep learning platform in China, has been officially open
Subpar is a utility for creating self-contained python executables. It is designed to work well with Bazel.
Subpar Subpar is a utility for creating self-contained python executables. It is designed to work well with Bazel. Status Subpar is currently owned by
A self-contained cryptographic library for Python
PyCryptodome PyCryptodome is a self-contained Python package of low-level cryptographic primitives. It supports Python 2.7, Python 3.4 and newer, and
A PyTorch Toolbox for Face Recognition
FaceX-Zoo FaceX-Zoo is a PyTorch toolbox for face recognition. It provides a training module with various supervisory heads and backbones towards stat
Open-AI's DALL-E for large scale training in mesh-tensorflow.
DALL-E in Mesh-Tensorflow [WIP] Open-AI's DALL-E in Mesh-Tensorflow. If this is similarly efficient to GPT-Neo, this repo should be able to train mode
Array is a functional mutable sequence inheriting from Python's built-in list.
funct.Array Array is a functional mutable sequence inheriting from Python's built-in list. Array provides 100+ higher-order methods and more functiona
Informer: Beyond Efficient Transformer for Long Sequence Time-Series Forecasting
Informer: Beyond Efficient Transformer for Long Sequence Time-Series Forecasting This is the origin Pytorch implementation of Informer in the followin
Rethinking Semantic Segmentation from a Sequence-to-Sequence Perspective with Transformers
Segmentation Transformer Implementation of Segmentation Transformer in PyTorch, a new model to achieve SOTA in semantic segmentation while using trans
Implementation of SE3-Transformers for Equivariant Self-Attention, in Pytorch.
SE3 Transformer - Pytorch Implementation of SE3-Transformers for Equivariant Self-Attention, in Pytorch. May be needed for replicating Alphafold2 resu
Implementation of Lie Transformer, Equivariant Self-Attention, in Pytorch
Lie Transformer - Pytorch (wip) Implementation of Lie Transformer, Equivariant Self-Attention, in Pytorch. Only the SE3 version will be present in thi
The algorithm performs a simple user registration (Name, CPF, E-mail and Telephone) in an Amazon RDS database and also performs the storage, training and facial recognition of the user's face to identify the users already registered in the system in a next time the user is seen.
Registration form with RDS AWS database and facial recognition via OpenCV The algorithm performs a simple user registration (Name, CPF, E-mail and Tel
CrossNER: Evaluating Cross-Domain Named Entity Recognition (AAAI-2021)
CrossNER is a fully-labeled collected of named entity recognition (NER) data spanning over five diverse domains (Politics, Natural Science, Music, Literature, and Artificial Intelligence) with specialized entity categories for different domains.
A framework for joint super-resolution and image synthesis, without requiring real training data
SynthSR This repository contains code to train a Convolutional Neural Network (CNN) for Super-resolution (SR), or joint SR and data synthesis. The met
Official PyTorch implementation for paper Context Matters: Graph-based Self-supervised Representation Learning for Medical Images
Context Matters: Graph-based Self-supervised Representation Learning for Medical Images Official PyTorch implementation for paper Context Matters: Gra
Backtest 1000s of minute-by-minute trading algorithms for training AI with automated pricing data from: IEX, Tradier and FinViz. Datasets and trading performance automatically published to S3 for building AI training datasets for teaching DNNs how to trade. Runs on Kubernetes and docker-compose. 150 million trading history rows generated from +5000 algorithms. Heads up: Yahoo's Finance API was disabled on 2019-01-03 https://developer.yahoo.com/yql/
Stock Analysis Engine Build and tune investment algorithms for use with artificial intelligence (deep neural networks) with a distributed stack for ru
Massively parallel self-organizing maps: accelerate training on multicore CPUs, GPUs, and clusters
Somoclu Somoclu is a massively parallel implementation of self-organizing maps. It exploits multicore CPUs, it is able to rely on MPI for distributing
A Python Library for Self Organizing Map (SOM)
SOMPY A Python Library for Self Organizing Map (SOM) As much as possible, the structure of SOM is similar to somtoolbox in Matlab. It has the followin
Simple, realtime visualization of neural network training performance.
pastalog Simple, realtime visualization server for training neural networks. Use with Lasagne, Keras, Tensorflow, Torch, Theano, and basically everyth
Yet Another Sequence Encoder - Encode sequences to vector of vector in python !
Yase Yet Another Sequence Encoder - encode sequences to vector of vectors in python ! Why Yase ? Yase enable you to encode any sequence which can be r
Determined: Deep Learning Training Platform
Determined: Deep Learning Training Platform Determined is an open-source deep learning training platform that makes building models fast and easy. Det
Deep Learning GPU Training System
DIGITS DIGITS (the Deep Learning GPU Training System) is a webapp for training deep learning models. The currently supported frameworks are: Caffe, To
A python library for self-supervised learning on images.
Lightly is a computer vision framework for self-supervised learning. We, at Lightly, are passionate engineers who want to make deep learning more effi
shiv is a command line utility for building fully self contained Python zipapps as outlined in PEP 441, but with all their dependencies included.
shiv shiv is a command line utility for building fully self-contained Python zipapps as outlined in PEP 441, but with all their dependencies included!