Python Deeplearning-models Resources

How Well Do Self-Supervised Models Transfer? This repository hosts the code for the experiments in the CVPR 2021 paper How Well Do Self-Supervised Mod

Res2Net The official pytorch implemention of the paper "Res2Net: A New Multi-scale Backbone Architecture" Our paper is accepted by IEEE Transactions o

Top2Vec is an algorithm for topic modeling and semantic search. It automatically detects topics present in text and generates jointly embedded topic, document and word vectors.

Unicorn on Rainbow Neural models of common sense. This repository is for the paper: Unicorn on Rainbow: A Universal Commonsense Reasoning Model on a N

This project is part of Eleuther AI's quest to create a massive repository of high quality text data for training language models.

P-tuning A novel method to tune language models. Codes and datasets for paper ``GPT understands, too''. How to use our code We have released the code

savior是一个能够进行快速集成算法模块并支持高性能部署的轻量开发框架。能够帮助将团队进行快速想法验证（PoC），避免重复的去github上找模型然后复现模型；能够帮助团队将功能进行流程拆解，很方便的提高分布式执行效率；能够有效减少代码冗余，减少不必要负担。

Viewflow Viewflow is a framework built on the top of Airflow that enables data scientists to create materialized views. It allows data scientists to f

The mljar-supervised is an Automated Machine Learning Python package that works with tabular data. I

ZhuSuan is a Python probabilistic programming library for Bayesian deep learning, which conjoins the complimentary advantages of Bayesian methods and

Edward is a Python library for probabilistic modeling, inference, and criticism. It is a testbed for fast experimentation and research with probabilis

Patsy is a Python library for describing statistical models (especially linear models, or models that have a linear component) and building design mat

Disclaimer This project is stable and being incubated for long-term support. It may contain new experimental code, for which APIs are subject to chang

pgmpy pgmpy is a python library for working with Probabilistic Graphical Models. Documentation and list of algorithms supported is at our official sit

Please consider citing the JMLR-MLOSS Manuscript if you've used pomegranate in your academic work! pomegranate is a package for building probabilistic

hmmlearn hmmlearn is a set of algorithms for unsupervised learning and inference of Hidden Markov Models. For supervised learning learning of HMMs and

skggm : Gaussian graphical models using the scikit-learn API In the last decade, learning networks that encode conditional independence relationships

PyTorch Implementation of Differentiable SDE Solvers This library provides stochastic differential equation (SDE) solvers with GPU support and efficie

(Generic) EfficientNets for PyTorch A 'generic' implementation of EfficientNet, MixNet, MobileNetV3, etc. that covers most of the compute/parameter ef

Rembg Virtual Greenscreen Edition is a tool to create a green screen matte for videos

Rembg Video Virtual Green Screen Edition

Hivemind: decentralized deep learning in PyTorch Hivemind is a PyTorch library to train large neural networks across the Internet. Its intended usage

Petastorm Contents Petastorm Installation Generating a dataset Plain Python API Tensorflow API Pytorch API Spark Dataset Converter API Analyzing petas

Horovod Horovod is a distributed deep learning training framework for TensorFlow, Keras, PyTorch, and Apache MXNet. The goal of Horovod is to make dis

Automated Time Series Models in Python (AtsPy) SSRN Report Easily develop state of the art time series models to forecast univariate data series. Simp

Auto_TS: Auto_TimeSeries Automatically build multiple Time Series models using a Single Line of Code. Now updated with Dask. Auto_timeseries is a comp

Time Series Made Easy in Python darts is a python library for easy manipulation and forecasting of time series. It contains a variety of models, from

pmdarima Pmdarima (originally pyramid-arima, for the anagram of 'py' + 'arima') is a statistical library designed to fill the void in Python's time se

arch Autoregressive Conditional Heteroskedasticity (ARCH) and other tools for financial econometrics, written in Python (with Cython and/or Numba used

Qlib is an AI-oriented quantitative investment platform, which aims to realize the potential, empower the research, and create the value of AI technol

Maths from examples - Learning advanced mathematical computations from examples This is the source code and data sets relevant to the paper Learning a

Diverse Image Captioning with Context-Object Split Latent Spaces This repository is the PyTorch implementation of the paper: Diverse Image Captioning

CDIoU-CDIoUloss CDIoU and CDIoU loss is like a convenient plug-in that can be used in multiple models. CDIoU and CDIoU loss have different excellent p

Reduce T5 model size by 3X and increase the inference speed up to 5X. Install Usage Details Functionalities Benchmarks Onnx model Quantized onnx model

merged_depth runs (1) AdaBins, (2) DiverseDepth, (3) MiDaS, (4) SGDepth, and (5) Monodepth2, and calculates a weighted-average per-pixel absolute dept

Hierarchical Pretraining: Research Repository This is a research repository for reproducing the results from the project "Self-supervised pretraining

EAST: An Efficient and Accurate Scene Text Detector Description: This version will be updated soon, please pay attention to this work. The motivation

Handwritten Text Recognition (OCR) with MXNet Gluon These notebooks have been created by Jonathan Chung, as part of his internship as Applied Scientis

SLM: Structural Language Models of Code This is an official implementation of the model described in: "Structural Language Models of Code" [PDF] To ap

MASR中文语音识别(pytorch版) 开箱即用 自行训练 使用与训练分离(增量训练) 识别率高 说明：因为每个人电脑机器不同，而且有些安装包安装起来比较麻烦，强烈建议直接用我编译好的docker环境跑 目前docker基础环境为ubuntu-cuda10.1-cudnn7-pytorch1.6.

BIGPrior: Towards Decoupling Learned Prior Hallucination and Data Fidelity in Image Restoration Authors: Majed El Helou, and Sabine Süsstrunk {Note: p

Neural Spatio-Temporal Point Processes [arxiv] Ricky T. Q. Chen, Brandon Amos, Maximilian Nickel Abstract. We propose a new class of parameterizations

Website • Docs • Blog • Twitter • Chat (Community & Support) • Tutorial • Mailing List Data Version Control or DVC is an open-source tool for data sci

Anytime Autoregressive Model Anytime Sampling for Autoregressive Models via Ordered Autoencoding , ICLR 21 Yilun Xu, Yang Song, Sahaj Gara, Linyuan Go

BIG-bench 🪑 The Beyond the Imitation Game Benchmark (BIG-bench) will be a collaborative benchmark intended to probe large language models, and extrap

Algo-ScriptML Python implementations of some of the fundamental Machine Learning models and algorithms from scratch. The goal of this project is not t

Create Django App 💛 We're a Django project starter on steroids! One-line command to create a Django app with all the dependencies auto-installed AND

ASEGAN: Speech Enhancement Generative Adversarial Network Based on Asymmetric AutoEncoder 中文版简介 Readme with English Version 介绍 基于SEGAN模型的改进版本，使用自主设计的非

Data Augmentation using Pre-trained Transformer Models Code associated with the Data Augmentation using Pre-trained Transformer Models paper Code cont

MMdnn MMdnn is a comprehensive and cross-framework tool to convert, visualize and diagnose deep learning (DL) models. The "MM" stands for model manage

Horovod Horovod is a distributed deep learning training framework for TensorFlow, Keras, PyTorch, and Apache MXNet. The goal of Horovod is to make dis

hsmmlearn hsmmlearn is a library for unsupervised learning of hidden semi-Markov models with explicit durations. It is a port of the hsmm package for

skggm : Gaussian graphical models using the scikit-learn API In the last decade, learning networks that encode conditional independence relationships

Netron is a viewer for neural network, deep learning and machine learning models. Netron supports ONNX (.onnx, .pb, .pbtxt), Keras (.h5, .keras), Tens

AI Explainability 360 (v0.2.1) The AI Explainability 360 toolkit is an open-source library that supports interpretability and explainability of datase

======== FairML: Auditing Black-Box Predictive Models FairML is a python toolbox auditing the machine learning models for bias. Description Predictive

Alibi is an open source Python library aimed at machine learning model inspection and interpretation. The focus of the library is to provide high-qual

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

tensorlm Generate Shakespeare poems with 4 lines of code. Installation tensorlm is written in / for Python 3.4+ and TensorFlow 1.1+ pip3 install tenso

torchvision The torchvision package consists of popular datasets, model architectures, and common image transformations for computer vision. Installat

Time series analysis today is an important cornerstone of quantitative science in many disciplines, including natural and life sciences as well as eco

pyGAM Generalized Additive Models in Python. Documentation Official pyGAM Documentation: Read the Docs Building interpretable models with Generalized

Highly interpretable, sklearn-compatible classifier based on decision rules This is a scikit-learn compatible wrapper for the Bayesian Rule List class

[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

OpenChat is opensource chatting framework for generative models.

A Python library that helps data scientists to infer causation rather than observing correlation.

django-wiki Django support The below table explains which Django versions are supported. Release Django Upgrade from 0.7.x 2.2, 3.0, 3.1 0.5 or 0.6 0.

Website • Docs • Blog • Twitter • Chat (Community & Support) • Tutorial • Mailing List Data Version Control or DVC is an open-source tool for data sci

Gino-Admin Docs (state: in process): Gino-Admin docs Play with Demo (current master 0.2.3) Gino-Admin demo (login: admin, pass: 1234) Admin

FastAPI Model Server Skeleton Serving machine learning models production-ready, fast, easy and secure powered by the great FastAPI by Sebastián Ramíre

improved-diffusion This is the codebase for Improved Denoising Diffusion Probabilistic Models. Usage This section of the README walks through how to t

SSD: Single Shot MultiBox Detector Introduction Here is my pytorch implementation of 2 models: SSD-Resnet50 and SSDLite-MobilenetV2.

BitPack is a practical tool that can efficiently save quantized neural network models with mixed bitwidth.

This repository provides the source code for training and testing state-of-the-art click-based interactive segmentation models with the official PyTorch implementation

Puzzle-CAM The official implementation of "Puzzle-CAM: Improved localization via matching partial and full features".

ForecastGA is a tool that combines a couple of popular libraries, Atspy and googleanalytics, with a few enhancements.

NFNet Pytorch Implementation This repo contains pretrained NFNet models F0-F6 with high ImageNet accuracy from the paper High-Performance Large-Scale

FastAPI Model Server Skeleton Serving machine learning models production-ready, fast, easy and secure powered by the great FastAPI by Sebastián Ramíre

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

Headliner Headliner is a sequence modeling library that eases the training and in particular, the deployment of custom sequence models for both resear

Sockeye This package contains the Sockeye project, an open-source sequence-to-sequence framework for Neural Machine Translation based on Apache MXNet

(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 Deep Learning NLP/NLU library by Intel® AI Lab Overview | Models | Installation | Examples | Documentation | Tutorials | Contributing NLP Architect

Fast-Bert New - Learning Rate Finder for Text Classification Training (borrowed with thanks from https://github.com/davidtvs/pytorch-lr-finder) Suppor

This repository contains custom pipes and models related to using spaCy for scientific documents. In particular, there is a custom tokenizer that adds

ParlAI (pronounced “par-lay”) is a python framework for sharing, training and testing dialogue models, from open-domain chitchat, to task-oriented dia

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

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. Website • Docs • Try it Now • Tutorials • Examples • Blog • Commun

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

⚠️ Checkout develop branch to see what is coming in pyannote.audio 2.0: a much smaller and cleaner codebase Python-first API (the good old pyannote-au

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

[Preprint] "TransGAN: Two Transformers Can Make One Strong GAN", Yifan Jiang, Shiyu Chang, Zhangyang Wang

Python scripts to detect faces using Python with the BlazeFace Tensorflow Lite models. Tested on Windows 10, Tensorflow 2.4.0 (Python 3.8).

⚡ Create CRUD routes with lighting speed ⚡ A dynamic FastAPI router that automatically creates CRUD routes for your models Documentation: https://fast

ec2-spot-converter This tool converts existing AWS EC2 instances back and forth between On-Demand and 'persistent' Spot billing models while preservin

Generate 3D meshes based on SDFs (signed distance functions) with a dirt simple Python API.

PyTorch Tabular aims to make Deep Learning with Tabular data easy and accessible to real-world cases and research alike.

The DeepSparse Engine is a CPU runtime that delivers unprecedented performance by taking advantage of natural sparsity within neural networks to reduce compute required as well as accelerate memory bound workloads. It is focused on model deployment and scaling machine learning pipelines, fitting seamlessly into your existing deployments as an inference backend.

InfoBERT: Improving Robustness of Language Models from An Information Theoretic Perspective This is the official code base for our ICLR 2021 paper