1482 Repositories
Python state-space-models Libraries
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
Named-entity recognition using neural networks. Easy-to-use and state-of-the-art results.
NeuroNER NeuroNER is a program that performs named-entity recognition (NER). Website: neuroner.com. This page gives step-by-step instructions to insta
Facilitating the design, comparison and sharing of deep text matching models.
MatchZoo Facilitating the design, comparison and sharing of deep text matching models. MatchZoo 是一个通用的文本匹配工具包,它旨在方便大家快速的实现、比较、以及分享最新的深度文本匹配模型。 🔥 News
🏖 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
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
:house_with_garden: Fast & easy transfer learning for NLP. Harvesting language models for the industry. Focus on Question Answering.
(Framework for Adapting Representation Models) What is it? FARM makes Transfer Learning with BERT & Co simple, fast and enterprise-ready. It's built u
A model library for exploring state-of-the-art deep learning topologies and techniques for optimizing Natural Language Processing neural networks
A Deep Learning NLP/NLU library by Intel® AI Lab Overview | Models | Installation | Examples | Documentation | Tutorials | Contributing NLP Architect
Super easy library for BERT based NLP models
Fast-Bert New - Learning Rate Finder for Text Classification Training (borrowed with thanks from https://github.com/davidtvs/pytorch-lr-finder) Suppor
A full spaCy pipeline and models for scientific/biomedical documents.
This repository contains custom pipes and models related to using spaCy for scientific documents. In particular, there is a custom tokenizer that adds
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
:mag: Transformers at scale for question answering & neural search. Using NLP via a modular Retriever-Reader-Pipeline. Supporting DPR, Elasticsearch, HuggingFace's Modelhub...
Haystack is an end-to-end framework for Question Answering & Neural search that enables you to ... ... ask questions in natural language and find gran
State of the Art Natural Language Processing
Spark NLP: State of the Art Natural Language Processing Spark NLP is a Natural Language Processing library built on top of Apache Spark ML. It provide
💥 Fast State-of-the-Art Tokenizers optimized for Research and Production
Provides an implementation of today's most used tokenizers, with a focus on performance and versatility. Main features: Train new vocabularies and tok
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
🤗Transformers: State-of-the-art Natural Language Processing for Pytorch and TensorFlow 2.0.
State-of-the-art Natural Language Processing for PyTorch and TensorFlow 2.0 🤗 Transformers provides thousands of pretrained models to perform tasks o
The open-source tool for building high-quality datasets and computer vision models
The open-source tool for building high-quality datasets and computer vision models. Website • Docs • Try it Now • Tutorials • Examples • Blog • Commun
Ludwig is a toolbox that allows to train and evaluate deep learning models without the need to write code.
Translated in 🇰🇷 Korean/ Ludwig is a toolbox that allows users to train and test deep learning models without the need to write code. It is built on
Turi Create simplifies the development of custom machine learning models.
Quick Links: Installation | Documentation | WWDC 2019 | WWDC 2018 Turi Create Check out our talks at WWDC 2019 and at WWDC 2018! Turi Create simplifie
The lightweight PyTorch wrapper for high-performance AI research. Scale your models, not the boilerplate.
The lightweight PyTorch wrapper for high-performance AI research. Scale your models, not the boilerplate. Website • Key Features • How To Use • Docs •
Statsmodels: statistical modeling and econometrics in Python
About statsmodels statsmodels is a Python package that provides a complement to scipy for statistical computations including descriptive statistics an
NO LONGER MAINTAINED - A Flask extension for creating simple ReSTful JSON APIs from SQLAlchemy models.
NO LONGER MAINTAINED This repository is no longer maintained due to lack of time. You might check out the fork https://github.com/mrevutskyi/flask-res
A dynamic FastAPI router that automatically creates CRUD routes for your models
⚡ Create CRUD routes with lighting speed ⚡ A dynamic FastAPI router that automatically creates CRUD routes for your models Documentation: https://fast
Automatic caching and invalidation for Django models through the ORM.
Cache Machine Cache Machine provides automatic caching and invalidation for Django models through the ORM. For full docs, see https://cache-machine.re
Declarative model lifecycle hooks, an alternative to Signals.
Django Lifecycle Hooks This project provides a @hook decorator as well as a base model and mixin to add lifecycle hooks to your Django models. Django'
Automatically deletes old file for FileField and ImageField. It also deletes files on models instance deletion.
Django Cleanup Features The django-cleanup app automatically deletes files for FileField, ImageField and subclasses. When a FileField's value is chang
A Django application that provides country choices for use with forms, flag icons static files, and a country field for models.
Django Countries A Django application that provides country choices for use with forms, flag icons static files, and a country field for models. Insta
Money fields for Django forms and models.
django-money A little Django app that uses py-moneyed to add support for Money fields in your models and forms. Django versions supported: 1.11, 2.1,
Django friendly finite state machine support
Django friendly finite state machine support django-fsm adds simple declarative state management for django models. If you need parallel task executio
Display machine state using Python3 with Flask.
Flask-State English | 简体中文 Flask-State is a lightweight chart plugin for displaying machine state data in your web application. Monitored Metric: CPU,
Generating images from caption and vice versa via CLIP-Guided Generative Latent Space Search
CLIP-GLaSS Repository for the paper Generating images from caption and vice versa via CLIP-Guided Generative Latent Space Search An in-browser demo is
PORORO: Platform Of neuRal mOdels for natuRal language prOcessing
PORORO: Platform Of neuRal mOdels for natuRal language prOcessing pororo performs Natural Language Processing and Speech-related tasks. It is easy to
Simple and rapid application development framework, built on top of Flask. includes detailed security, auto CRUD generation for your models, google charts and much more. Demo (login with guest/welcome) - http://flaskappbuilder.pythonanywhere.com/
Flask App Builder Simple and rapid application development framework, built on top of Flask. includes detailed security, auto CRUD generation for your
The Web framework for perfectionists with deadlines.
Django Django is a high-level Python Web framework that encourages rapid development and clean, pragmatic design. Thanks for checking it out. All docu
An implementation of model parallel GPT-3-like models on GPUs, based on the DeepSpeed library. Designed to be able to train models in the hundreds of billions of parameters or larger.
GPT-NeoX An implementation of model parallel GPT-3-like models on GPUs, based on the DeepSpeed library. Designed to be able to train models in the hun
Easy to use, state-of-the-art Neural Machine Translation for 100+ languages
EasyNMT - Easy to use, state-of-the-art Neural Machine Translation This package provides easy to use, state-of-the-art machine translation for more th
A machine learning benchmark of in-the-wild distribution shifts, with data loaders, evaluators, and default models.
WILDS is a benchmark of in-the-wild distribution shifts spanning diverse data modalities and applications, from tumor identification to wildlife monitoring to poverty mapping.
A dynamic FastAPI router that automatically creates CRUD routes for your models
⚡ Create CRUD routes with lighting speed ⚡ A dynamic FastAPI router that automatically creates CRUD routes for your models
Code, Models and Datasets for OpenViDial Dataset
OpenViDial This repo contains downloading instructions for the OpenViDial dataset in 《OpenViDial: A Large-Scale, Open-Domain Dialogue Dataset with Vis
CVPR 2021 Challenge on Super-Resolution Space
Learning the Super-Resolution Space Challenge NTIRE 2021 at CVPR Learning the Super-Resolution Space challenge is held as a part of the 6th edition of
Command line animations based on the state of the system
shell-emotions Command line animations based on the state of the system for Linux or Windows 10 The ascii animations were created using a modified ver
State of the Art Neural Networks for Deep Learning
pyradox This python library helps you with implementing various state of the art neural networks in a totally customizable fashion using Tensorflow 2
Build Text Rerankers with Deep Language Models
Reranker is a lightweight, effective and efficient package for training and deploying deep languge model reranker in information retrieval (IR), question answering (QA) and many other natural language processing (NLP) pipelines. The training procedure follows our ECIR paper Rethink Training of BERT Rerankers in Multi-Stage Retrieval Pipeline using a localized constrastive esimation (LCE) loss.
RTS3D: Real-time Stereo 3D Detection from 4D Feature-Consistency Embedding Space for Autonomous Driving
RTS3D: Real-time Stereo 3D Detection from 4D Feature-Consistency Embedding Space for Autonomous Driving (AAAI2021). RTS3D is efficiency and accuracy s
Client library to download and publish models and other files on the huggingface.co hub
huggingface_hub Client library to download and publish models and other files on the huggingface.co hub Do you have an open source ML library? We're l
profile tools for pytorch nn models
nnprof Introduction nnprof is a profile tool for pytorch neural networks. Features multi profile mode: nnprof support 4 profile mode: Layer level, Ope
For holding anime-related object classification and detection models
Animesion An end-to-end framework for anime-related object classification, detection, segmentation, and other models. Update: 01/22/2020. Due to time-
Generate saved_model, tfjs, tf-trt, EdgeTPU, CoreML, quantized tflite and .pb from .tflite.
tflite2tensorflow Generate saved_model, tfjs, tf-trt, EdgeTPU, CoreML, quantized tflite and .pb from .tflite. 1. Supported Layers No. TFLite Layer TF
The official implementation of NeMo: Neural Mesh Models of Contrastive Features for Robust 3D Pose Estimation [ICLR-2021]. https://arxiv.org/pdf/2101.12378.pdf
NeMo: Neural Mesh Models of Contrastive Features for Robust 3D Pose Estimation [ICLR-2021] Release Notes The offical PyTorch implementation of NeMo, p
[ICLR 2021] "Neural Architecture Search on ImageNet in Four GPU Hours: A Theoretically Inspired Perspective" by Wuyang Chen, Xinyu Gong, Zhangyang Wang
Neural Architecture Search on ImageNet in Four GPU Hours: A Theoretically Inspired Perspective [PDF] Wuyang Chen, Xinyu Gong, Zhangyang Wang In ICLR 2
The fastest way to visualize GradCAM with your Keras models.
VizGradCAM VizGradCam is the fastest way to visualize GradCAM in Keras models. GradCAM helps with providing visual explainability of trained models an
Applications using the GTN library and code to reproduce experiments in "Differentiable Weighted Finite-State Transducers"
gtn_applications An applications library using GTN. Current examples include: Offline handwriting recognition Automatic speech recognition Installing
Official implementation of AAAI-21 paper "Label Confusion Learning to Enhance Text Classification Models"
Description: This is the official implementation of our AAAI-21 accepted paper Label Confusion Learning to Enhance Text Classification Models. The str
Reinforcement Learning Coach by Intel AI Lab enables easy experimentation with state of the art Reinforcement Learning algorithms
Coach Coach is a python reinforcement learning framework containing implementation of many state-of-the-art algorithms. It exposes a set of easy-to-us
Official Python client for the MonkeyLearn API. Build and consume machine learning models for language processing from your Python apps.
MonkeyLearn API for Python Official Python client for the MonkeyLearn API. Build and run machine learning models for language processing from your Pyt
WordPress models and views for Django.
django-wordpress Models and views for reading a WordPress database. Compatible with WordPress version 3.5+. django-wordpress is a project of ISL and t
Statsmodels: statistical modeling and econometrics in Python
About statsmodels statsmodels is a Python package that provides a complement to scipy for statistical computations including descriptive statistics an
Deep recommender models using PyTorch.
Spotlight uses PyTorch to build both deep and shallow recommender models. By providing both a slew of building blocks for loss functions (various poin
A Python Library for Simple Models and Containers Persisted in Redis
Redisco Python Containers and Simple Models for Redis Description Redisco allows you to store objects in Redis. It is inspired by the Ruby library Ohm
Named-entity recognition using neural networks. Easy-to-use and state-of-the-art results.
NeuroNER NeuroNER is a program that performs named-entity recognition (NER). Website: neuroner.com. This page gives step-by-step instructions to insta
Colibri core is an NLP tool as well as a C++ and Python library for working with basic linguistic constructions such as n-grams and skipgrams (i.e patterns with one or more gaps, either of fixed or dynamic size) in a quick and memory-efficient way. At the core is the tool ``colibri-patternmodeller`` whi ch allows you to build, view, manipulate and query pattern models.
Colibri Core by Maarten van Gompel, [email protected], Radboud University Nijmegen Licensed under GPLv3 (See http://www.gnu.org/licenses/gpl-3.0.html
Create UIs for prototyping your machine learning model in 3 minutes
Note: We just launched Hosted, where anyone can upload their interface for permanent hosting. Check it out! Welcome to Gradio Quickly create customiza
Automates Machine Learning Pipeline with Feature Engineering and Hyper-Parameters Tuning :rocket:
MLJAR Automated Machine Learning Documentation: https://supervised.mljar.com/ Source Code: https://github.com/mljar/mljar-supervised Table of Contents
Machine learning, in numpy
numpy-ml Ever wish you had an inefficient but somewhat legible collection of machine learning algorithms implemented exclusively in NumPy? No? Install
Visualizer for neural network, deep learning, and machine learning models
Netron is a viewer for neural network, deep learning and machine learning models. Netron supports ONNX (.onnx, .pb, .pbtxt), Keras (.h5, .keras), Tens
Turi Create simplifies the development of custom machine learning models.
Quick Links: Installation | Documentation | WWDC 2019 | WWDC 2018 Turi Create Check out our talks at WWDC 2019 and at WWDC 2018! Turi Create simplifie
Machine Learning From Scratch. Bare bones NumPy implementations of machine learning models and algorithms with a focus on accessibility. Aims to cover everything from linear regression to deep learning.
Machine Learning From Scratch About Python implementations of some of the fundamental Machine Learning models and algorithms from scratch. The purpose
Toolbox of models, callbacks, and datasets for AI/ML researchers.
Pretrained SOTA Deep Learning models, callbacks and more for research and production with PyTorch Lightning and PyTorch Website • Installation • Main
The lightweight PyTorch wrapper for high-performance AI research. Scale your models, not the boilerplate.
The lightweight PyTorch wrapper for high-performance AI research. Scale your models, not the boilerplate. Website • Key Features • How To Use • Docs •
Python Library for learning (Structure and Parameter) and inference (Statistical and Causal) in Bayesian Networks.
pgmpy pgmpy is a python library for working with Probabilistic Graphical Models. Documentation and list of algorithms supported is at our official sit
Fast, flexible and easy to use probabilistic modelling in Python.
Please consider citing the JMLR-MLOSS Manuscript if you've used pomegranate in your academic work! pomegranate is a package for building probabilistic
pyhsmm - library for approximate unsupervised inference in Bayesian Hidden Markov Models (HMMs) and explicit-duration Hidden semi-Markov Models (HSMMs), focusing on the Bayesian Nonparametric extensions, the HDP-HMM and HDP-HSMM, mostly with weak-limit approximations.
Bayesian inference in HSMMs and HMMs This is a Python library for approximate unsupervised inference in Bayesian Hidden Markov Models (HMMs) and expli
Easy and comprehensive assessment of predictive power, with support for neuroimaging features
Documentation: https://raamana.github.io/neuropredict/ News As of v0.6, neuropredict now supports regression applications i.e. predicting continuous t
Automatically Build Multiple ML Models with a Single Line of Code. Created by Ram Seshadri. Collaborators Welcome. Permission Granted upon Request.
Auto-ViML Automatically Build Variant Interpretable ML models fast! Auto_ViML is pronounced "auto vimal" (autovimal logo created by Sanket Ghanmare) N
a delightful machine learning tool that allows you to train, test and use models without writing code
igel A delightful machine learning tool that allows you to train/fit, test and use models without writing code Note I'm also working on a GUI desktop
💡 Learnergy is a Python library for energy-based machine learning models.
Learnergy: Energy-based Machine Learners Welcome to Learnergy. Did you ever reach a bottleneck in your computational experiments? Are you tired of imp
Quickly and easily create / train a custom DeepDream model
Dream-Creator This project aims to simplify the process of creating a custom DeepDream model by using pretrained GoogleNet models and custom image dat
Build fully-functioning computer vision models with PyTorch
Detecto is a Python package that allows you to build fully-functioning computer vision and object detection models with just 5 lines of code. Inferenc
H2O is an Open Source, Distributed, Fast & Scalable Machine Learning Platform: Deep Learning, Gradient Boosting (GBM) & XGBoost, Random Forest, Generalized Linear Modeling (GLM with Elastic Net), K-Means, PCA, Generalized Additive Models (GAM), RuleFit, Support Vector Machine (SVM), Stacked Ensembles, Automatic Machine Learning (AutoML), etc.
H2O H2O is an in-memory platform for distributed, scalable machine learning. H2O uses familiar interfaces like R, Python, Scala, Java, JSON and the Fl
Hook and simulate global keyboard events on Windows and Linux.
keyboard Take full control of your keyboard with this small Python library. Hook global events, register hotkeys, simulate key presses and much more.
A Django application that provides country choices for use with forms, flag icons static files, and a country field for models.
Django Countries A Django application that provides country choices for use with forms, flag icons static files, and a country field for models. Insta
Automatic caching and invalidation for Django models through the ORM.
Cache Machine Cache Machine provides automatic caching and invalidation for Django models through the ORM. For full docs, see https://cache-machine.re
A lightweight, object-oriented finite state machine implementation in Python with many extensions
transitions A lightweight, object-oriented state machine implementation in Python with many extensions. Compatible with Python 2.7+ and 3.0+. Installa