1599 Repositories
Python model-optimization Libraries
A Python Automated Machine Learning tool that optimizes machine learning pipelines using genetic programming.
Master status: Development status: Package information: TPOT stands for Tree-based Pipeline Optimization Tool. Consider TPOT your Data Science Assista
Probabilistic programming framework that facilitates objective model selection for time-varying parameter models.
Time series analysis today is an important cornerstone of quantitative science in many disciplines, including natural and life sciences as well as eco
Module for statistical learning, with a particular emphasis on time-dependent modelling
Operating system Build Status Linux/Mac Windows tick tick is a Python 3 module for statistical learning, with a particular emphasis on time-dependent
50% faster, 50% less RAM Machine Learning. Numba rewritten Sklearn. SVD, NNMF, PCA, LinearReg, RidgeReg, Randomized, Truncated SVD/PCA, CSR Matrices all 50+% faster
[Due to the time taken @ uni, work + hell breaking loose in my life, since things have calmed down a bit, will continue commiting!!!] [By the way, I'm
A modular active learning framework for Python
Modular Active Learning framework for Python3 Page contents Introduction Active learning from bird's-eye view modAL in action From zero to one in a fe
High performance, easy-to-use, and scalable machine learning (ML) package, including linear model (LR), factorization machines (FM), and field-aware factorization machines (FFM) for Python and CLI interface.
What is xLearn? xLearn is a high performance, easy-to-use, and scalable machine learning package that contains linear model (LR), factorization machin
Implementation of COCO-LM, Correcting and Contrasting Text Sequences for Language Model Pretraining, in Pytorch
COCO LM Pretraining (wip) Implementation of COCO-LM, Correcting and Contrasting Text Sequences for Language Model Pretraining, in Pytorch. They were a
Official code for paper "Optimization for Oriented Object Detection via Representation Invariance Loss".
Optimization for Oriented Object Detection via Representation Invariance Loss By Qi Ming, Zhiqiang Zhou, Lingjuan Miao, Xue Yang, and Yunpeng Dong. Th
Open source platform for the machine learning lifecycle
MLflow: A Machine Learning Lifecycle Platform MLflow is a platform to streamline machine learning development, including tracking experiments, packagi
FastAPI Skeleton App to serve machine learning models production-ready.
FastAPI Model Server Skeleton Serving machine learning models production-ready, fast, easy and secure powered by the great FastAPI by Sebastián Ramíre
MazeRL is an application oriented Deep Reinforcement Learning (RL) framework
MazeRL is an application oriented Deep Reinforcement Learning (RL) framework, addressing real-world decision problems. Our vision is to cover the complete development life cycle of RL applications ranging from simulation engineering up to agent development, training and deployment.
A demo of Prometheus+Grafana for monitoring an ML model served with FastAPI.
ml-monitoring Jeremy Jordan This repository provides an example setup for monitoring an ML system deployed on Kubernetes.
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
Model search is a framework that implements AutoML algorithms for model architecture search at scale
Model search (MS) is a framework that implements AutoML algorithms for model architecture search at scale. It aims to help researchers speed up their exploration process for finding the right model architecture for their classification problems (i.e., DNNs with different types of layers).
Gaphor is the simple modeling tool
Gaphor Gaphor is a UML and SysML modeling application written in Python. It is designed to be easy to use, while still being powerful. Gaphor implemen
naked is a Python tool which allows you to strip a model and only keep what matters for making predictions.
naked is a Python tool which allows you to strip a model and only keep what matters for making predictions. The result is a pure Python function with no third-party dependencies that you can simply copy/paste wherever you wish.
BitPack is a practical tool to efficiently save ultra-low precision/mixed-precision quantized models.
BitPack is a practical tool that can efficiently save quantized neural network models with mixed bitwidth.
ForecastGA is a Python tool to forecast Google Analytics data using several popular time series models.
ForecastGA is a tool that combines a couple of popular libraries, Atspy and googleanalytics, with a few enhancements.
计算机视觉中用到的注意力模块和其他即插即用模块PyTorch Implementation Collection of Attention Module and Plug&Play Module
PyTorch实现多种计算机视觉中网络设计中用到的Attention机制,还收集了一些即插即用模块。由于能力有限精力有限,可能很多模块并没有包括进来,有任何的建议或者改进,可以提交issue或者进行PR。
Kindle is an easy model build package for PyTorch.
Kindle is an easy model build package for PyTorch. Building a deep learning model became so simple that almost all model can be made by copy and paste from other existing model codes. So why code? when we can simply build a model with yaml markup file. Kindle builds a model with no code but yaml file which its method is inspired from YOLOv5.
FastAPI Skeleton App to serve machine learning models production-ready.
FastAPI Model Server Skeleton Serving machine learning models production-ready, fast, easy and secure powered by the great FastAPI by Sebastián Ramíre
NLP library designed for reproducible experimentation management
Welcome to the Transfer NLP library, a framework built on top of PyTorch to promote reproducible experimentation and Transfer Learning in NLP You can
NeuralQA: A Usable Library for Question Answering on Large Datasets with BERT
NeuralQA: A Usable Library for (Extractive) Question Answering on Large Datasets with BERT Still in alpha, lots of changes anticipated. View demo on n
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
Scikit-learn style model finetuning for NLP
Scikit-learn style model finetuning for NLP Finetune is a library that allows users to leverage state-of-the-art pretrained NLP models for a wide vari
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
Python package to easily retrain OpenAI's GPT-2 text-generating model on new texts
gpt-2-simple A simple Python package that wraps existing model fine-tuning and generation scripts for OpenAI's GPT-2 text generation model (specifical
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
🛸 Use pretrained transformers like BERT, XLNet and GPT-2 in spaCy
spacy-transformers: Use pretrained transformers like BERT, XLNet and GPT-2 in spaCy This package provides spaCy components and architectures to use tr
:mag: End-to-End Framework for building natural language search interfaces to data by utilizing Transformers and the State-of-the-Art of NLP. Supporting DPR, Elasticsearch, HuggingFace’s Modelhub and much more!
Haystack is an end-to-end framework that enables you to build powerful and production-ready pipelines for different search use cases. Whether you want
💥 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
🤗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
commonfate 📦commonfate 📦 - Common Fate Model and Transform.
Common Fate Transform and Model for Python This package is a python implementation of the Common Fate Transform and Model to be used for audio source
Inner ear models for Python
cochlea cochlea is a collection of inner ear models. All models are easily accessible as Python functions. They take sound signal as input and return
Pyroomacoustics is a package for audio signal processing for indoor applications. It was developed as a fast prototyping platform for beamforming algorithms in indoor scenarios.
Summary Pyroomacoustics is a software package aimed at the rapid development and testing of audio array processing algorithms. The content of the pack
MongoEngine flask extension with WTF model forms support
Flask-MongoEngine Info: MongoEngine for Flask web applications. Repository: https://github.com/MongoEngine/flask-mongoengine About Flask-MongoEngine i
A tool to convert AWS EC2 instances back and forth between On-Demand and Spot billing models.
ec2-spot-converter This tool converts existing AWS EC2 instances back and forth between On-Demand and 'persistent' Spot billing models while preservin
Code for the Shortformer model, from the paper by Ofir Press, Noah A. Smith and Mike Lewis.
Shortformer This repository contains the code and the final checkpoint of the Shortformer model. This file explains how to run our experiments on the
Efficient 3D Backbone Network for Temporal Modeling
VoV3D is an efficient and effective 3D backbone network for temporal modeling implemented on top of PySlowFast. Diverse Temporal Aggregation and
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
A flexible free and unlimited python tool to translate between different languages in a simple way using multiple translators.
deep-translator Translation for humans A flexible FREE and UNLIMITED tool to translate between different languages in a simple way using multiple tran
NLP library designed for reproducible experimentation management
Welcome to the Transfer NLP library, a framework built on top of PyTorch to promote reproducible experimentation and Transfer Learning in NLP You can
NeuralQA: A Usable Library for Question Answering on Large Datasets with BERT
NeuralQA: A Usable Library for (Extractive) Question Answering on Large Datasets with BERT Still in alpha, lots of changes anticipated. View demo on n
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
Scikit-learn style model finetuning for NLP
Scikit-learn style model finetuning for NLP Finetune is a library that allows users to leverage state-of-the-art pretrained NLP models for a wide vari
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
Python package to easily retrain OpenAI's GPT-2 text-generating model on new texts
gpt-2-simple A simple Python package that wraps existing model fine-tuning and generation scripts for OpenAI's GPT-2 text generation model (specifical
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
🛸 Use pretrained transformers like BERT, XLNet and GPT-2 in spaCy
spacy-transformers: Use pretrained transformers like BERT, XLNet and GPT-2 in spaCy This package provides spaCy components and architectures to use tr
: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
💥 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
🤗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
torchbearer: A model fitting library for PyTorch
Note: We're moving to PyTorch Lightning! Read about the move here. From the end of February, torchbearer will no longer be actively maintained. We'll
High performance, easy-to-use, and scalable machine learning (ML) package, including linear model (LR), factorization machines (FM), and field-aware factorization machines (FFM) for Python and CLI interface.
What is xLearn? xLearn is a high performance, easy-to-use, and scalable machine learning package that contains linear model (LR), factorization machin
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'
A django model and form field for normalised phone numbers using python-phonenumbers
django-phonenumber-field A Django library which interfaces with python-phonenumbers to validate, pretty print and convert phone numbers. python-phonen
Improved Django model inheritance with automatic downcasting
Polymorphic Models for Django Django-polymorphic simplifies using inherited models in Django projects. When a query is made at the base model, the inh
A reusable Django model field for storing ad-hoc JSON data
jsonfield jsonfield is a reusable model field that allows you to store validated JSON, automatically handling serialization to and from the database.
Store model history and view/revert changes from admin site.
django-simple-history django-simple-history stores Django model state on every create/update/delete. This app supports the following combinations of D
Django model mixins and utilities.
django-model-utils Django model mixins and utilities. django-model-utils supports Django 2.2+. This app is available on PyPI. Getting Help Documentati
django-reversion is an extension to the Django web framework that provides version control for model instances.
django-reversion django-reversion is an extension to the Django web framework that provides version control for model instances. Requirements Python 3
MongoEngine flask extension with WTF model forms support
Flask-MongoEngine Info: MongoEngine for Flask web applications. Repository: https://github.com/MongoEngine/flask-mongoengine About Flask-MongoEngine i
Library to scrape and clean web pages to create massive datasets.
lazynlp A straightforward library that allows you to crawl, clean up, and deduplicate webpages to create massive monolingual datasets. Using this libr
NLP Core Library and Model Zoo based on PaddlePaddle 2.0
PaddleNLP 2.0拥有丰富的模型库、简洁易用的API与高性能的分布式训练的能力,旨在为飞桨开发者提升文本建模效率,并提供基于PaddlePaddle 2.0的NLP领域最佳实践。
Only a Matter of Style: Age Transformation Using a Style-Based Regression Model
Only a Matter of Style: Age Transformation Using a Style-Based Regression Model The task of age transformation illustrates the change of an individual
Trankit is a Light-Weight Transformer-based Python Toolkit for Multilingual Natural Language Processing
Trankit: A Light-Weight Transformer-based Python Toolkit for Multilingual Natural Language Processing Trankit is a light-weight Transformer-based Pyth
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
Distributed Asynchronous Hyperparameter Optimization better than HyperOpt.
UltraOpt : Distributed Asynchronous Hyperparameter Optimization better than HyperOpt. UltraOpt is a simple and efficient library to minimize expensive
AIST++ API This repo contains starter code for using the AIST++ dataset.
AIST++ API This repo contains starter code for using the AIST++ dataset. To download the dataset or explore details of this dataset, please go to our
Joint detection and tracking model named DEFT, or ``Detection Embeddings for Tracking.
DEFT: Detection Embeddings for Tracking DEFT: Detection Embeddings for Tracking, Mohamed Chaabane, Peter Zhang, J. Ross Beveridge, Stephen O'Hara
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
PyTorch implementation of "A Full-Band and Sub-Band Fusion Model for Real-Time Single-Channel Speech Enhancement."
FullSubNet This Git repository for the official PyTorch implementation of "A Full-Band and Sub-Band Fusion Model for Real-Time Single-Channel Speech E
This is a repository for a No-Code object detection inference API using the OpenVINO. It's supported on both Windows and Linux Operating systems.
OpenVINO Inference API This is a repository for an object detection inference API using the OpenVINO. It's supported on both Windows and Linux Operati
Create animations for the optimization trajectory of neural nets
Animating the Optimization Trajectory of Neural Nets loss-landscape-anim lets you create animated optimization path in a 2D slice of the loss landscap
KoBART model on huggingface transformers
KoBART-Transformers SKT에서 공개한 KoBART를 편리하게 사용할 수 있게 transformers로 포팅하였습니다. Install (Optional) BartModel과 PreTrainedTokenizerFast를 이용하면 설치하실 필요 없습니다. p
Spectrum is an AI that uses machine learning to generate Rap song lyrics
Spectrum Spectrum is an AI that uses deep learning to generate rap song lyrics. View Demo Report Bug Request Feature Open In Colab About The Project S
Torchserve server using a YoloV5 model running on docker with GPU and static batch inference to perform production ready inference.
Yolov5 running on TorchServe (GPU compatible) ! This is a dockerfile to run TorchServe for Yolo v5 object detection model. (TorchServe (PyTorch librar
Repository to run object detection on a model trained on an autonomous driving dataset.
Autonomous Driving Object Detection on the Raspberry Pi 4 Description of Repository This repository contains code and instructions to configure the ne
Debugging, monitoring and visualization for Python Machine Learning and Data Science
Welcome to TensorWatch TensorWatch is a debugging and visualization tool designed for data science, deep learning and reinforcement learning from Micr
A Python package implementing a new model for text classification with visualization tools for Explainable AI :octocat:
A Python package implementing a new model for text classification with visualization tools for Explainable AI 🍣 Online live demos: http://tworld.io/s
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
🐦 Opytimizer is a Python library consisting of meta-heuristic optimization techniques.
Opytimizer: A Nature-Inspired Python Optimizer Welcome to Opytimizer. Did you ever reach a bottleneck in your computational experiments? Are you tired
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
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
Simple, but essential Bayesian optimization package
BayesO: A Bayesian optimization framework in Python Simple, but essential Bayesian optimization package. http://bayeso.org Online documentation Instal
A Sklearn-like Framework for Hyperparameter Tuning and AutoML in Deep Learning projects. Finally have the right abstractions and design patterns to properly do AutoML. Let your pipeline steps have hyperparameter spaces. Enable checkpoints to cut duplicate calculations. Go from research to production environment easily.
Neuraxle Pipelines Code Machine Learning Pipelines - The Right Way. Neuraxle is a Machine Learning (ML) library for building machine learning pipeline
MiraiML: asynchronous, autonomous and continuous Machine Learning in Python
MiraiML Mirai: future in japanese. MiraiML is an asynchronous engine for continuous & autonomous machine learning, built for real-time usage. Usage In
Model Serving Made Easy
The easiest way to build Machine Learning APIs BentoML makes moving trained ML models to production easy: Package models trained with any ML framework
High performance, easy-to-use, and scalable machine learning (ML) package, including linear model (LR), factorization machines (FM), and field-aware factorization machines (FFM) for Python and CLI interface.
What is xLearn? xLearn is a high performance, easy-to-use, and scalable machine learning package that contains linear model (LR), factorization machin
A modular active learning framework for Python
Modular Active Learning framework for Python3 Page contents Introduction Active learning from bird's-eye view modAL in action From zero to one in a fe
A web-based application for quick, scalable, and automated hyperparameter tuning and stacked ensembling in Python.
Xcessiv Xcessiv is a tool to help you create the biggest, craziest, and most excessive stacked ensembles you can think of. Stacked ensembles are simpl
Home repository for the Regularized Greedy Forest (RGF) library. It includes original implementation from the paper and multithreaded one written in C++, along with various language-specific wrappers.
Regularized Greedy Forest Regularized Greedy Forest (RGF) is a tree ensemble machine learning method described in this paper. RGF can deliver better r
A Python Automated Machine Learning tool that optimizes machine learning pipelines using genetic programming.
Master status: Development status: Package information: TPOT stands for Tree-based Pipeline Optimization Tool. Consider TPOT your Data Science Assista
Spearmint Bayesian optimization codebase
Spearmint Spearmint is a software package to perform Bayesian optimization. The Software is designed to automatically run experiments (thus the code n
Model serving at scale
Run inference at scale Cortex is an open source platform for large-scale machine learning inference workloads. Workloads Realtime APIs - respond to pr
[UNMAINTAINED] Automated machine learning for analytics & production
auto_ml Automated machine learning for production and analytics Installation pip install auto_ml Getting started from auto_ml import Predictor from au
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
Genetic Algorithm, Particle Swarm Optimization, Simulated Annealing, Ant Colony Optimization Algorithm,Immune Algorithm, Artificial Fish Swarm Algorithm, Differential Evolution and TSP(Traveling salesman)
scikit-opt Swarm Intelligence in Python (Genetic Algorithm, Particle Swarm Optimization, Simulated Annealing, Ant Colony Algorithm, Immune Algorithm,A
An open source framework that provides a simple, universal API for building distributed applications. Ray is packaged with RLlib, a scalable reinforcement learning library, and Tune, a scalable hyperparameter tuning library.
Ray provides a simple, universal API for building distributed applications. Ray is packaged with the following libraries for accelerating machine lear