1179 Repositories
Python urdf-models Libraries
Machine Learning Model to predict the payment date of an invoice when it gets created in the system.
Payment-Date-Prediction Machine Learning Model to predict the payment date of an invoice when it gets created in the system.
darts is a Python library for easy manipulation and forecasting of time series.
A python library for easy manipulation and forecasting of time series.
A collection of Classical Chinese natural language processing models, including Classical Chinese related models and resources on the Internet.
GuwenModels: 古文自然语言处理模型合集, 收录互联网上的古文相关模型及资源. A collection of Classical Chinese natural language processing models, including Classical Chinese related models and resources on the Internet.
Unofficial PyTorch implementation of Neural Additive Models (NAM) by Agarwal, et al.
nam-pytorch Unofficial PyTorch implementation of Neural Additive Models (NAM) by Agarwal, et al. [abs, pdf] Installation You can access nam-pytorch vi
A large-scale video dataset for the training and evaluation of 3D human pose estimation models
ASPset-510 (Australian Sports Pose Dataset) is a large-scale video dataset for the training and evaluation of 3D human pose estimation models. It contains 17 different amateur subjects performing 30 sports-related actions each, for a total of 510 action clips.
A large-scale video dataset for the training and evaluation of 3D human pose estimation models
ASPset-510 ASPset-510 (Australian Sports Pose Dataset) is a large-scale video dataset for the training and evaluation of 3D human pose estimation mode
Using pretrained language models for biomedical knowledge graph completion.
LMs for biomedical KG completion This repository contains code to run the experiments described in: Scientific Language Models for Biomedical Knowledg
PyTorch implementation and pretrained models for XCiT models. See XCiT: Cross-Covariance Image Transformer
Official code Cross-Covariance Image Transformer (XCiT)
We envision models that are pre-trained on a vast range of domain-relevant tasks to become key for molecule property prediction
We envision models that are pre-trained on a vast range of domain-relevant tasks to become key for molecule property prediction. This repository aims to give easy access to state-of-the-art pre-trained models.
PyTorch implementation and pretrained models for XCiT models. See XCiT: Cross-Covariance Image Transformer
Cross-Covariance Image Transformer (XCiT) PyTorch implementation and pretrained models for XCiT models. See XCiT: Cross-Covariance Image Transformer L
Official Pytorch implementation of paper "Reverse Engineering of Generative Models: Inferring Model Hyperparameters from Generated Images"
Reverse_Engineering_GMs Official Pytorch implementation of paper "Reverse Engineering of Generative Models: Inferring Model Hyperparameters from Gener
Code for "LoRA: Low-Rank Adaptation of Large Language Models"
LoRA: Low-Rank Adaptation of Large Language Models This repo contains the implementation of LoRA in GPT-2 and steps to replicate the results in our re
Official PyTorch implementation and pretrained models of the paper Self-Supervised Classification Network
Self-Classifier: Self-Supervised Classification Network Official PyTorch implementation and pretrained models of the paper Self-Supervised Classificat
This project is based on RIFE and aims to make RIFE more practical for users by adding various features and design new models
This project is based on RIFE and aims to make RIFE more practical for users by adding various features and design new models. Because improving the PSNR index is not compatible with subjective effects, we hope this part of work and our academic research are independent of each other.
The codes and models in 'Gaze Estimation using Transformer'.
GazeTR We provide the code of GazeTR-Hybrid in "Gaze Estimation using Transformer". We recommend you to use data processing codes provided in GazeHub.
Code + pre-trained models for the paper Keeping Your Eye on the Ball Trajectory Attention in Video Transformers
Motionformer This is an official pytorch implementation of paper Keeping Your Eye on the Ball: Trajectory Attention in Video Transformers. In this rep
Repository for publicly available deep learning models developed in Rosetta community
trRosetta2 This package contains deep learning models and related scripts used by Baker group in CASP14. Installation Linux/Mac clone the package git
A Python package for the mathematical modeling of infectious diseases via compartmental models
A Python package for the mathematical modeling of infectious diseases via compartmental models. Originally designed for epidemiologists, epispot can be adapted for almost any type of modeling scenario.
[CVPR 2021] Teachers Do More Than Teach: Compressing Image-to-Image Models (CAT)
CAT arXiv Pytorch implementation of our method for compressing image-to-image models. Teachers Do More Than Teach: Compressing Image-to-Image Models Q
MERLOT: Multimodal Neural Script Knowledge Models
merlot MERLOT: Multimodal Neural Script Knowledge Models MERLOT is a model for learning what we are calling "neural script knowledge" -- representatio
Code implementation of "Sparsity Probe: Analysis tool for Deep Learning Models"
Sparsity Probe: Analysis tool for Deep Learning Models This repository is a limited implementation of Sparsity Probe: Analysis tool for Deep Learning
Official PyTorch implementation for FastDPM, a fast sampling algorithm for diffusion probabilistic models
Official PyTorch implementation for "On Fast Sampling of Diffusion Probabilistic Models". FastDPM generation on CIFAR-10, CelebA, and LSUN datasets. S
Source code and dataset for ACL2021 paper: "ERICA: Improving Entity and Relation Understanding for Pre-trained Language Models via Contrastive Learning".
ERICA Source code and dataset for ACL2021 paper: "ERICA: Improving Entity and Relation Understanding for Pre-trained Language Models via Contrastive L
Python API for working with RESQML models
resqpy: Python API for working with RESQML models Introduction resqpy is a pure python package which provides a programming interface (API) for readin
A framework for analyzing computer vision models with simulated data
3DB: A framework for analyzing computer vision models with simulated data Paper Quickstart guide Blog post Installation Follow instructions on: https:
This code reproduces the results of the paper, "Measuring Data Leakage in Machine-Learning Models with Fisher Information"
Fisher Information Loss This repository contains code that can be used to reproduce the experimental results presented in the paper: Awni Hannun, Chua
Adversarial Attacks on Probabilistic Autoregressive Forecasting Models.
Attack-Probabilistic-Models This is the source code for Adversarial Attacks on Probabilistic Autoregressive Forecasting Models. This repository contai
[CVPR 2021] "The Lottery Tickets Hypothesis for Supervised and Self-supervised Pre-training in Computer Vision Models" Tianlong Chen, Jonathan Frankle, Shiyu Chang, Sijia Liu, Yang Zhang, Michael Carbin, Zhangyang Wang
The Lottery Tickets Hypothesis for Supervised and Self-supervised Pre-training in Computer Vision Models Codes for this paper The Lottery Tickets Hypo
The official codes of "Semi-supervised Models are Strong Unsupervised Domain Adaptation Learners".
SSL models are Strong UDA learners Introduction This is the official code of paper "Semi-supervised Models are Strong Unsupervised Domain Adaptation L
Code for our ACL 2021 (Findings) Paper - Fingerprinting Fine-tuned Language Models in the wild .
🌳 Fingerprinting Fine-tuned Language Models in the wild This is the code and dataset for our ACL 2021 (Findings) Paper - Fingerprinting Fine-tuned La
FEDn is an open-source, modular and ML-framework agnostic framework for Federated Machine Learning
FEDn is an open-source, modular and ML-framework agnostic framework for Federated Machine Learning (FedML) developed and maintained by Scaleout Systems. FEDn enables highly scalable cross-silo and cross-device use-cases over FEDn networks.
Pytorch Implementation of DiffSinger: Diffusion Acoustic Model for Singing Voice Synthesis (TTS Extension)
DiffSinger - PyTorch Implementation PyTorch implementation of DiffSinger: Diffusion Acoustic Model for Singing Voice Synthesis (TTS Extension). Status
Pytorch implementation of Generative Models as Distributions of Functions 🌿
Generative Models as Distributions of Functions This repo contains code to reproduce all experiments in Generative Models as Distributions of Function
Boosting Monocular Depth Estimation Models to High-Resolution via Content-Adaptive Multi-Resolution Merging
Boosting Monocular Depth Estimation Models to High-Resolution via Content-Adaptive Multi-Resolution Merging This repository contains an implementation
Inferoxy is a service for quick deploying and using dockerized Computer Vision models.
Inferoxy is a service for quick deploying and using dockerized Computer Vision models. It's a core of EORA's Computer Vision platform Vision Hub that runs on top of AWS EKS.
simpleT5 is built on top of PyTorch-lightning⚡️ and Transformers🤗 that lets you quickly train your T5 models.
Quickly train T5 models in just 3 lines of code + ONNX support simpleT5 is built on top of PyTorch-lightning ⚡️ and Transformers 🤗 that lets you quic
tf2onnx - Convert TensorFlow, Keras and Tflite models to ONNX.
tf2onnx converts TensorFlow (tf-1.x or tf-2.x), tf.keras and tflite models to ONNX via command line or python api.
This repo contains the official code and pre-trained models for the Dynamic Vision Transformer (DVT).
Dynamic-Vision-Transformer (Pytorch) This repo contains the official code and pre-trained models for the Dynamic Vision Transformer (DVT). Not All Ima
Repository for the "Gotta Go Fast When Generating Data with Score-Based Models" paper
Gotta Go Fast When Generating Data with Score-Based Models This repo contains the official implementation for the paper Gotta Go Fast When Generating
SparseML is a libraries for applying sparsification recipes to neural networks with a few lines of code, enabling faster and smaller models
SparseML is a toolkit that includes APIs, CLIs, scripts and libraries that apply state-of-the-art sparsification algorithms such as pruning and quantization to any neural network. General, recipe-driven approaches built around these algorithms enable the simplification of creating faster and smaller models for the ML performance community at large.
Anonymize BLM Protest Images
Anonymize BLM Protest Images This repository automates @BLMPrivacyBot, a Twitter bot that shows the anonymized images to help keep protesters safe. Us
This project provides an unsupervised framework for mining and tagging quality phrases on text corpora with pretrained language models (KDD'21).
UCPhrase: Unsupervised Context-aware Quality Phrase Tagging To appear on KDD'21...[pdf] This project provides an unsupervised framework for mining and
This repository contains the implementations related to the experiments of a set of publicly available datasets that are used in the time series forecasting research space.
TSForecasting This repository contains the implementations related to the experiments of a set of publicly available datasets that are used in the tim
TensorFlow Decision Forests (TF-DF) is a collection of state-of-the-art algorithms for the training, serving and interpretation of Decision Forest models.
TensorFlow Decision Forests (TF-DF) is a collection of state-of-the-art algorithms for the training, serving and interpretation of Decision Forest models. The library is a collection of Keras models and supports classification, regression and ranking. TF-DF is a TensorFlow wrapper around the Yggdrasil Decision Forests C++ libraries. Models trained with TF-DF are compatible with Yggdrasil Decision Forests' models, and vice versa.
True Few-Shot Learning with Language Models
This codebase supports using language models (LMs) for true few-shot learning: learning to perform a task using a limited number of examples from a single task distribution.
Code for the paper "Adapting Monolingual Models: Data can be Scarce when Language Similarity is High"
Wietse de Vries • Martijn Bartelds • Malvina Nissim • Martijn Wieling Adapting Monolingual Models: Data can be Scarce when Language Similarity is High
An evaluation toolkit for voice conversion models.
Voice-conversion-evaluation An evaluation toolkit for voice conversion models. Sample test pair Generate the metadata for evaluating models. The direc
covid question answering datasets and fine tuned models
Covid-QA Fine tuned models for question answering on Covid-19 data. Hosted Inference This model has been contributed to huggingface.Click here to see
Generate lookml for views from dbt models
dbt2looker Use dbt2looker to generate Looker view files automatically from dbt models. Features Column descriptions synced to looker Dimension for eac
Finding an Unsupervised Image Segmenter in each of your Deep Generative Models
Finding an Unsupervised Image Segmenter in each of your Deep Generative Models Description Recent research has shown that numerous human-interpretable
Lipstick ain't enough: Beyond Color-Matching for In-the-Wild Makeup Transfer (CVPR 2021)
Table of Content Introduction Datasets Getting Started Requirements Usage Example Training & Evaluation CPM: Color-Pattern Makeup Transfer CPM is a ho
Apache Liminal is an end-to-end platform for data engineers & scientists, allowing them to build, train and deploy machine learning models in a robust and agile way
Apache Liminals goal is to operationalise the machine learning process, allowing data scientists to quickly transition from a successful experiment to an automated pipeline of model training, validation, deployment and inference in production. Liminal provides a Domain Specific Language to build ML workflows on top of Apache Airflow.
A Lucid Framework for Transparent and Interpretable Machine Learning Models.
Currently a Beta-Version lucidmode is an open-source, low-code and lightweight Python framework for transparent and interpretable machine learning mod
An evaluation toolkit for voice conversion models.
Voice-conversion-evaluation An evaluation toolkit for voice conversion models. Sample test pair Generate the metadata for evaluating models. The direc
XtremeDistil framework for distilling/compressing massive multilingual neural network models to tiny and efficient models for AI at scale
XtremeDistilTransformers for Distilling Massive Multilingual Neural Networks ACL 2020 Microsoft Research [Paper] [Video] Releasing [XtremeDistilTransf
Language models are open knowledge graphs ( non official implementation )
language-models-are-knowledge-graphs-pytorch Language models are open knowledge graphs ( work in progress ) A non official reimplementation of Languag
Pretrained models for Jax/Flax: StyleGAN2, GPT2, VGG, ResNet.
Pretrained models for Jax/Flax: StyleGAN2, GPT2, VGG, ResNet.
PyTorch Implementation for AAAI'21 "Do Response Selection Models Really Know What's Next? Utterance Manipulation Strategies for Multi-turn Response Selection"
UMS for Multi-turn Response Selection Implements the model described in the following paper Do Response Selection Models Really Know What's Next? Utte
Code and models used in "MUSS Multilingual Unsupervised Sentence Simplification by Mining Paraphrases".
Multilingual Unsupervised Sentence Simplification Code and pretrained models to reproduce experiments in "MUSS: Multilingual Unsupervised Sentence Sim
Ever felt tired after preprocessing the dataset, and not wanting to write any code further to train your model? Ever encountered a situation where you wanted to record the hyperparameters of the trained model and able to retrieve it afterward? Models Playground is here to help you do that. Models playground allows you to train your models right from the browser.
Models Playground 🗂️ Upload a Preprocessed Dataset 🌠 Choose whether to perform Classification or Regression 🦹 Enter the Dependent Variable ?
This is the codebase for Diffusion Models Beat GANS on Image Synthesis.
This is the codebase for Diffusion Models Beat GANS on Image Synthesis.
A collection of GNN-based fake news detection models.
This repo includes the Pytorch-Geometric implementation of a series of Graph Neural Network (GNN) based fake news detection models. All GNN models are implemented and evaluated under the User Preference-aware Fake News Detection (UPFD) framework. The fake news detection problem is instantiated as a graph classification task under the UPFD framework.
LaneDet is an open source lane detection toolbox based on PyTorch that aims to pull together a wide variety of state-of-the-art lane detection models
LaneDet is an open source lane detection toolbox based on PyTorch that aims to pull together a wide variety of state-of-the-art lane detection models. Developers can reproduce these SOTA methods and build their own methods.
a CLI that provides a generic automation layer for assessing the security of ML models
Counterfit About | Getting Started | Learn More | Acknowledgments | Contributing | Trademarks | Contact Us -------------------------------------------
Objective of the repository is to learn and build machine learning models using Pytorch. 30DaysofML Using Pytorch
30 Days Of Machine Learning Using Pytorch Objective of the repository is to learn and build machine learning models using Pytorch. List of Algorithms
a CLI that provides a generic automation layer for assessing the security of ML models
a CLI that provides a generic automation layer for assessing the security of ML models
Repository for XLM-T, a framework for evaluating multilingual language models on Twitter data
This is the XLM-T repository, which includes data, code and pre-trained multilingual language models for Twitter. XLM-T - A Multilingual Language Mode
Tilted Empirical Risk Minimization (ICLR '21)
Tilted Empirical Risk Minimization This repository contains the implementation for the paper Tilted Empirical Risk Minimization ICLR 2021 Empirical ri
Official repository for the ICLR 2021 paper Evaluating the Disentanglement of Deep Generative Models with Manifold Topology
Official repository for the ICLR 2021 paper Evaluating the Disentanglement of Deep Generative Models with Manifold Topology Sharon Zhou, Eric Zelikman
Parrot is a paraphrase based utterance augmentation framework purpose built to accelerate training NLU models
Parrot is a paraphrase based utterance augmentation framework purpose built to accelerate training NLU models. A paraphrase framework is more than just a paraphrasing model.
Pytorch-Named-Entity-Recognition-with-BERT
BERT NER Use google BERT to do CoNLL-2003 NER ! Train model using Python and Inference using C++ ALBERT-TF2.0 BERT-NER-TENSORFLOW-2.0 BERT-SQuAD Requi
A modular framework for vision & language multimodal research from Facebook AI Research (FAIR)
MMF is a modular framework for vision and language multimodal research from Facebook AI Research. MMF contains reference implementations of state-of-t
Neural building blocks for speaker diarization: speech activity detection, speaker change detection, overlapped speech detection, speaker embedding
⚠️ 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
A PyTorch Implementation of End-to-End Models for Speech-to-Text
speech Speech is an open-source package to build end-to-end models for automatic speech recognition. Sequence-to-sequence models with attention, Conne
Interpretable Models for NLP using PyTorch
This repo is deprecated. Please find the updated package here. https://github.com/EdGENetworks/anuvada Anuvada: Interpretable Models for NLP using PyT
An open source framework for seq2seq models in PyTorch.
pytorch-seq2seq Documentation This is a framework for sequence-to-sequence (seq2seq) models implemented in PyTorch. The framework has modularized and
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
Seamlessly integrate pydantic models in your Sphinx documentation.
Seamlessly integrate pydantic models in your Sphinx documentation.
SMPLpix: Neural Avatars from 3D Human Models
subject0_validation_poses.mp4 Left: SMPL-X human mesh registered with SMPLify-X, middle: SMPLpix render, right: ground truth video. SMPLpix: Neural Av
Generative Models for Graph-Based Protein Design
Graph-Based Protein Design This repo contains code for Generative Models for Graph-Based Protein Design by John Ingraham, Vikas Garg, Regina Barzilay
[EMNLP 2020] Keep CALM and Explore: Language Models for Action Generation in Text-based Games
Contextual Action Language Model (CALM) and the ClubFloyd Dataset Code and data for paper Keep CALM and Explore: Language Models for Action Generation
Codes for our paper "SentiLARE: Sentiment-Aware Language Representation Learning with Linguistic Knowledge" (EMNLP 2020)
SentiLARE: Sentiment-Aware Language Representation Learning with Linguistic Knowledge Introduction SentiLARE is a sentiment-aware pre-trained language
Meta Language-Specific Layers in Multilingual Language Models
Meta Language-Specific Layers in Multilingual Language Models This repo contains the source codes for our paper On Negative Interference in Multilingu
Django queries
Djaq Djaq - pronounced “Jack” - provides an instant remote API to your Django models data with a powerful query language. No server-side code beyond t
QuickAI is a Python library that makes it extremely easy to experiment with state-of-the-art Machine Learning models.
QuickAI is a Python library that makes it extremely easy to experiment with state-of-the-art Machine Learning models.
An Easy-to-use, Modular and Prolongable package of deep-learning based Named Entity Recognition Models.
DeepNER An Easy-to-use, Modular and Prolongable package of deep-learning based Named Entity Recognition Models. This repository contains complex Deep
QuickAI is a Python library that makes it extremely easy to experiment with state-of-the-art Machine Learning models.
QuickAI is a Python library that makes it extremely easy to experiment with state-of-the-art Machine Learning models.
ArviZ is a Python package for exploratory analysis of Bayesian models
ArviZ (pronounced "AR-vees") is a Python package for exploratory analysis of Bayesian models. Includes functions for posterior analysis, data storage, model checking, comparison and diagnostics
Task-based datasets, preprocessing, and evaluation for sequence models.
SeqIO: Task-based datasets, preprocessing, and evaluation for sequence models. SeqIO is a library for processing sequential data to be fed into downst
Create a netflix-like service using Django, React.js, & More.
Create a netflix-like service using Django. Learn advanced Django techniques to achieve amazing results like never before.
TorchFlare is a simple, beginner-friendly, and easy-to-use PyTorch Framework train your models effortlessly.
TorchFlare TorchFlare is a simple, beginner-friendly and an easy-to-use PyTorch Framework train your models without much effort. It provides an almost
Learning Energy-Based Models by Diffusion Recovery Likelihood
Learning Energy-Based Models by Diffusion Recovery Likelihood Ruiqi Gao, Yang Song, Ben Poole, Ying Nian Wu, Diederik P. Kingma Paper: https://arxiv.o
🤗 The largest hub of ready-to-use NLP datasets for ML models with fast, easy-to-use and efficient data manipulation tools
🤗 The largest hub of ready-to-use NLP datasets for ML models with fast, easy-to-use and efficient data manipulation tools
MMGeneration is a powerful toolkit for generative models, based on PyTorch and MMCV.
Documentation: https://mmgeneration.readthedocs.io/ Introduction English | 简体中文 MMGeneration is a powerful toolkit for generative models, especially f
Attack classification models with transferability, black-box attack; unrestricted adversarial attacks on imagenet
Attack classification models with transferability, black-box attack; unrestricted adversarial attacks on imagenet, CVPR2021 安全AI挑战者计划第六期:ImageNet无限制对抗攻击 决赛第四名(team name: Advers)
OCTIS: Comparing Topic Models is Simple! A python package to optimize and evaluate topic models (accepted at EACL2021 demo track)
OCTIS : Optimizing and Comparing Topic Models is Simple! OCTIS (Optimizing and Comparing Topic models Is Simple) aims at training, analyzing and compa
A simple way to train and use PyTorch models with multi-GPU, TPU, mixed-precision
🤗 Accelerate was created for PyTorch users who like to write the training loop of PyTorch models but are reluctant to write and maintain the boilerplate code needed to use multi-GPUs/TPU/fp16.
Pytorch implementation of our paper under review — Lottery Jackpots Exist in Pre-trained Models
Lottery Jackpots Exist in Pre-trained Models (Paper Link) Requirements Python = 3.7.4 Pytorch = 1.6.1 Torchvision = 0.4.1 Reproduce the Experiment
This repository contains the code for "Generating Datasets with Pretrained Language Models".
Datasets from Instructions (DINO 🦕 ) This repository contains the code for Generating Datasets with Pretrained Language Models. The paper introduces
Sequence-to-sequence framework with a focus on Neural Machine Translation based on Apache MXNet
Sequence-to-sequence framework with a focus on Neural Machine Translation based on Apache MXNet