Python Model-parallel Resources

This repository contains the official PyTorch implementation of the "CRF-RNN" semantic image segmentation method, published in the ICCV 2015

Python inverse kinematics for your robot model based on Pinocchio.

IMLE-Net: An Interpretable Multi-level Multi-channel Model for ECG Classification The repostiory consists of the code, results and data set links for

This machine learning model was developed for House Prices - Advanced Regression Techniques competition in Kaggle by using several machine learning models such as Random Forest, XGBoost and LightGBM.

R-YOLOv4 This is a PyTorch-based R-YOLOv4 implementation which combines YOLOv4 model and loss function from R3Det for arbitrary oriented object detect

ONNX-GLPDepth - Python scripts for performing monocular depth estimation using the GLPDepth model in ONNX

Shashank Ojha, Sabrina Button, Abdellah Ghassel, Joshua Gonzales "Reduce Reuse R

Anomaly-detection-Feature-Selection Evaluate on three different ML model for feature selection using Breast cancer data. ML models: SVM, KNN and MLP.

Breast cancer is been classified into benign tumour and malignant tumour. Logistic regression is applied in this model.

Breast Cancer Classification Model is applied on a different dataset

VOODOO Revealing supercooled liquid beyond lidar attenuation Explore the docs » Report Bug · Request Feature Table of Contents About The Project Built

News-Recommendation-system-using-Bert4Rec-model Bert4rec for news Recommendation

Deep learning based model for Cyro ET Sub-tomogram-Detection High degree of stru

This is a model made out of Neural Network specifically a Convolutional Neural Network model. This was done with a pre-built dataset from the tensorflow and keras packages. There are other alternative libraries that can be used for this purpose, one of which is the PyTorch library.

SUMO - Slim U-Net trained on MODA Implementation of the SUMO (Slim U-Net trained on MODA) model as described in: TODO: add reference to paper once ava

Training-a-deep-learning-model-on-the-noisy-CIFAR-dataset This repository contai

CovidcasePrediction A machine learning model for Covid case prediction Problem Statement Using regression algorithms we can able to track the active c

GraphNLI: A Graph-based Natural Language Inference Model for Polarity Prediction in Online Debates Vibhor Agarwal, Sagar Joglekar, Anthony P. Young an

bct_file_generator_for_EasyGSH The aim is to extract timeseries water level 2D information for any designed boundaries within the EasyGSH model domain

This repository contains the raw dataset used in NHNet [1] for the task of News Story Headline Generation. The code of data processing and training is available under Tensorflow Models - NHNet.

Used for data processing in machine learning, and help us to construct ML model more easily from scratch. Can be used in linear model, logistic regression model, and decision tree.

Contrastive Learning for Neural Topic Model This repository contains the impleme

A Microsoft Azure Web App project named Covid 19 Predictor using Machine learning Model (Random Forest Classifier Model ) that helps the user to identify whether someone is showing positive Covid symptoms or not by simply inputting certain values like oxygen level , breath rate , age, Vaccination done or not etc. with the help of kaggle database.

Mortgage-Application-Analysis Create a machine learning model which will predict if the mortgage will be approved or not based on 5 variables: age, in

Low-resource-Machine-Translation This repository contains the code for the project relative to the course Deep Natural Language Processing. The goal o

NLP - Movie review sentiment analysis The colab notebook contains the code for building a LSTM Recurrent Neural Network that gives 87-88% accuracy on

Jarvis_voiceAssistance This is a working model for which I have used python. This model can: 1)Play a video or song on youtube. 2)Tell us time. 3)Tell

spaCy-wrap: For Wrapping fine-tuned transformers in spaCy pipelines spaCy-wrap is minimal library intended for wrapping fine-tuned transformers from t

Driver Analysis with Factors and Forests: An Automated Data Science Tool using Python 📊

Transformers are all you need In this workshop we will be exploring NLP state of the art transformers, with SOTA models like T5 and BERT, then build a

MLOps The MLOps is the process of continuous integration and continuous delivery of Machine Learning artifacts as a software product, keeping it insid

ruCLIP-SB RuCLIP-SB (Russian Contrastive Language–Image Pretraining SWIN-BERT) is a multimodal model for obtaining images and text similarities and re

Ray Vector Environment Wrapper You would like to use Ray to vectorize your environment but you don't want to use RLLib ? You came to the right place !

FlatTN This repository contains code accompanying the paper "An End-to-End Chinese Text Normalization Model based on Rule-Guided Flat-Lattice Transfor

SPLADE 🍴 + 🥄 = 🔎 This repository contains the weights for four models as well as the code for running inference for our two papers: [v1]: SPLADE: S

Gesture_recognition The training data consists of a few hundred videos categorised into one of the five classes. Each video (typically 2-3 seconds lon

This program takes and input of an ECG in European Data Format (EDF) and outputs the classification for heartbeats into normal vs different types of arrhythmia . It uses a deep learning model for classification purposes.

RVM_onnx_compose RobustVideoMatting and background composing in one model by using onnxruntime. Usage pip install -r requirements.txt python infer_cam

Fake_news_classification A model to classify a piece of news as REAL or FAKE. This python project of detecting fake news deals with fake and real news

MusicYOLO MusicYOLO framework uses the object detection model, YOLOX, to locate notes in the spectrogram. Its performance on the ISMIR2014 dataset, MI

ae_attendances_modelling This repository contains the raw data and a python notebook to ingest historical A&E attendance data and then use a simple Pr

GPT-2 Catalan playground and scripts to train a GPT-2 model either from scrath or from another pretrained model.

YOLOv5 Auto Annotator Annotate datasets with a semi-trained or fully trained YOLOv5 model Prerequisites Ubuntu =20.04 Python =3.7 System dependencie

High-fidelity 3D Model Compression based on Key Spheres This repository contains the implementation of the paper: Yuanzhan Li, Yuqi Liu, Yujie Lu, Siy

HealthGen: Conditional EHR Time Series Generation This repository contains the implementation of the HealthGen model, a generative model to synthesize

MetaTTE: a Meta-Learning Based Travel Time Estimation Model for Multi-city Scenarios This is the official TensorFlow implementation of MetaTTE in the

CNN-Filter-DB An Empirical Investigation of Model-to-Model Distribution Shifts in Trained Convolutional Filters Paul Gavrikov, Janis Keuper Paper: htt

Open-Source Toolbox for Infrastructures Probabilistic Deterioration Modelling OpenIPDM is a MATLAB open-source platform that stands for infrastructure

UPMT Generate fine-tuning samples & Fine-tuning the model & Generate samples by transferring Note On See main.py as an example: from model import PopM

CvT2DistilGPT2 Improving Chest X-Ray Report Generation by Leveraging Warm-Starting This repository houses the implementation of CvT2DistilGPT2 from [1

Combinatorial model of ligand-receptor binding The binding of ligands to receptors is the starting point for many import signal pathways within a cell

PaRT: Parallel Learning for Robust and Transparent AI This repository contains the code for PaRT, an algorithm for training a base network on multiple

Official code of Team Yao at Multi-Modal-Fact-Verification-2022 A Multi-Modal Fact Verification dataset released as part of the De-Factify workshop in

Variational Model Inversion Attacks Kuan-Chieh Wang, Yan Fu, Ke Li, Ashish Khisti, Richard Zemel, Alireza Makhzani Most commands are in run_scripts. W

MIL Model Agnostic Interpretability This repo contains the code for "Model Agnostic Interpretability for Multiple Instance Learning". Overview Executa

shap-hypetune A python package for simultaneous Hyperparameters Tuning and Features Selection for Gradient Boosting Models. Overview Hyperparameters t

We provide a notebook that shows how to import the IITB English-Hindi Parallel Corpus from the HuggingFace datasets repository. The notebook also shows how to segment the corpus using BPE tokenization which can be used to train an English-Hindi MT System.

The purpose of this project is create a classification model capable of accurately predicting the price of secondhand cars. The data used for model building is open source and has been added to this repository. Most packages used are usually pre-installed in most developed environments and tools like collab, jupyter, etc. This can be useful for people looking to enhance the way the code their predicitve models and efficient ways to deal with tabular data!

Style transfer between images was performed using the VGG19 model. The necessary codes, libraries and all other information of this project are available below

EasyRequests EasyRequests is a minimalistic HTTP-Request Library that wraps aiohttp and asyncio in a small package that allows for sequential, paralle

Description This library provides an abstraction to perform Model Versioning using Weight & Biases. Features Version a new trained model Promote a mod

A cut down version of QUANT containing just the model in Python (QUANTPy)

SAS: Self-Augmentation Strategy for Language Model Pre-training This repository

GreaseLM: Graph REASoning Enhanced Language Models This repo provides the source code & data of our paper "GreaseLM: Graph REASoning Enhanced Language

EdiBERT, a generative model for image editing EdiBERT is a generative model based on a bi-directional transformer, suited for image manipulation. The

The current workflow simulates brain functional connectivity (FC) from structural connectivity (SC) with a neural mass model. Gradient descent is applied to optimize the parameters in the neural mass model.

RoNER RoNER is a Named Entity Recognition model based on a pre-trained BERT transformer model trained on RONECv2. It is meant to be an easy to use, hi

Hello from magnus Magnus provides four capabilities for data teams: Compute execution plan: A DAG representation of work that you want to get done. In

Estimating-Loan-Default-Probability IBA ML2 Mid-project / Kaggle Competition This porject is intented to build the most accurate model for predicting

Toward Model Interpretability in Medical NLP LING380: Topics in Computational Linguistics Final Project James Cross ([email protected]) and Daniel Kim

aCe - Data-Centric Parallel Programming Decoupling domain science from performance optimization. DaCe is a parallel programming framework that takes c

FCN_MSCOCO_Food_Segmentation Simple keras FCN Encoder/Decoder model for MS-COCO (food subset) segmentation Input data: [http://mscoco.org/dataset/#ove

ademxapp Visual applications by the University of Adelaide In designing our Model A, we did not over-optimize its structure for efficiency unless it w

Static Features Classifier This is a static features classifier for Point-Could

Equipped customers with insights about their EVs Hourly energy consumption and helped predict future charging behavior using LSTM model. Designed sample dashboard with insights and recommendation for customers.

Generative design of breakwaters usign deep convolutional neural network as a surrogate model This repository contains the code for the paper "Generat

Disaster Classificiation using CNNs bunnysaini/Disaster-Classificiation Goal To prepare an image processing model to classify the type of disaster bas

Pynomial - a lightweight python library for implementing the many confidence intervals for the risk parameter of a binomial model

Optuna is an automatic hyperparameter optimization software framework, particularly designed for machine learning. It features an imperative, define-by-run style user API.

ParaMonte is a serial/parallel library of Monte Carlo routines for sampling mathematical objective functions of arbitrary-dimensions, in particular, the posterior distributions of Bayesian models in data science, Machine Learning, and scientific inference, with the design goal of unifying the automation (of Monte Carlo simulations), user-friendliness (of the library), accessibility (from multiple programming environments), high-performance (at runtime), and scalability (across many parallel processors).

HistoSeg : Quick attention with multi-loss function for multi-structure segmentation in digital histology images Histological Image Segmentation This

sequitur sequitur is a library that lets you create and train an autoencoder for sequential data in just two lines of code. It implements three differ

Omnivore: A Single Model for Many Visual Modalities [paper][website] OMNIVORE is a single vision model for many different visual modalities. It learns

Product Recognition on Store Shelves Description You can read the task description here. Report You can read and download our report here. Step A - Mu

Django Pickled Model Django pickled model provides you a model with dynamic data types. a field can store any value in any type. You can store Integer

Starter code: Kaggle Toxic Comment Classification Challenge More competitions 🎇 Check collection of public projects 🎁 , where you can find multiple

Language Models as Zero-Shot Planners: Extracting Actionable Knowledge for Embodied Agents [Project Page] [Paper] [Video] Wenlong Huang1, Pieter Abbee

event-driven-model-serving Unified API of Apache Kafka and Google PubSub 1. Proj

Deep-Learning-Project This Deep Learning Model Predicts that from which disease you are suffering. This Project Covers the Topics of Deep Learning Int

nextPARS, a novel Illumina-based implementation of in-vitro parallel probing of RNA structures. Here you will find the scripts necessary to produce th

Blackstone Blackstone is a spaCy model and library for processing long-form, unstructured legal text. Blackstone is an experimental research project f

Grover is a model for Neural Fake News -- both generation and detection. However, it probably can also be used for other generation tasks.

Prompt Tuning This is the code to reproduce the experiments from the EMNLP 2021 paper "The Power of Scale for Parameter-Efficient Prompt Tuning" (Lest

NCSR: Noise Conditional Flow Model for Learning the Super-Resolution Space Official NCSR training PyTorch Code for the CVPR2021 workshop paper "Noise

Consensus Learning from Heterogeneous Objectives for One-Class Collaborative Filtering This repository provides the source code of "Consensus Learning

To model the probability of a soccer coach leave his/her team during Campeonato Brasileiro for 10 chosen teams and considering years 2018, 2019 and 2020.

A novel dual model approach for categorization of unbalanced skin lesion image classes (Presented technical paper 📃)

PyTorch Implementation of "Progressive Distillation for Fast Sampling of Diffusion Models(v-diffusion)" Unofficial PyTorch Implementation of Progressi

Finetune the base 64 px GLIDE-text2im model from OpenAI on your own image-text dataset

Common machine learning models' hyperparameter tuning This repo is for a collection of hyper-parameter tuning for "common" machine learning models, in