1887 Repositories
Python model-training Libraries
CvT2DistilGPT2 is an encoder-to-decoder model that was developed for chest X-ray report generation.
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
Combinatorial model of ligand-receptor binding The binding of ligands to receptors is the starting point for many import signal pathways within a cell
Framework for training options with different attention mechanism and using them to solve downstream tasks.
Using Attention in HRL Framework for training options with different attention mechanism and using them to solve downstream tasks. Requirements GPU re
Identifying a Training-Set Attack’s Target Using Renormalized Influence Estimation
Identifying a Training-Set Attack’s Target Using Renormalized Influence Estimation By: Zayd Hammoudeh and Daniel Lowd Paper: Arxiv Preprint Coming soo
Official code of Team Yao at Multi-Modal-Fact-Verification-2022
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
Post-training Quantization for Neural Networks with Provable Guarantees
Post-training Quantization for Neural Networks with Provable Guarantees Authors: Jinjie Zhang ([email protected]), Yixuan Zhou ([email protected]) and Ray
Check out the StyleGAN repo and place it in the same directory hierarchy as the present repo
Variational Model Inversion Attacks Kuan-Chieh Wang, Yan Fu, Ke Li, Ashish Khisti, Richard Zemel, Alireza Makhzani Most commands are in run_scripts. W
Model Agnostic Interpretability for Multiple Instance Learning
MIL Model Agnostic Interpretability This repo contains the code for "Model Agnostic Interpretability for Multiple Instance Learning". Overview Executa
Hyperparameters tuning and features selection are two common steps in every machine learning pipeline.
shap-hypetune A python package for simultaneous Hyperparameters Tuning and Features Selection for Gradient Boosting Models. Overview Hyperparameters t
A classification model capable of accurately predicting the price of secondhand cars
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
Style transfer between images was performed using the VGG19 model. The necessary codes, libraries and all other information of this project are available below
This library provides an abstraction to perform Model Versioning using Weight & Biases.
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)
A cut down version of QUANT containing just the model in Python (QUANTPy)
SAS: Self-Augmentation Strategy for Language Model Pre-training
SAS: Self-Augmentation Strategy for Language Model Pre-training This repository
This repo provides the source code & data of our paper "GreaseLM: Graph REASoning Enhanced Language Models"
GreaseLM: Graph REASoning Enhanced Language Models This repo provides the source code & data of our paper "GreaseLM: Graph REASoning Enhanced Language
EdiBERT is a generative model based on a bi-directional transformer, suited for image manipulation
EdiBERT, a generative model for image editing EdiBERT is a generative model based on a bi-directional transformer, suited for image manipulation. The
Revisiting Weakly Supervised Pre-Training of Visual Perception Models
SWAG: Supervised Weakly from hashtAGs This repository contains SWAG models from the paper Revisiting Weakly Supervised Pre-Training of Visual Percepti
Cycle Self-Training for Domain Adaptation (NeurIPS 2021)
CST Code release for "Cycle Self-Training for Domain Adaptation" (NeurIPS 2021) Prerequisites torch=1.7.0 torchvision qpsolvers numpy prettytable tqd
A hybrid framework (neural mass model + ML) for SC-to-FC prediction
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 is a Named Entity Recognition model based on a pre-trained BERT transformer model trained on RONECv2
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
This porject is intented to build the most accurate model for predicting the porbability of loan default
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
Toward Model Interpretability in Medical NLP LING380: Topics in Computational Linguistics Final Project James Cross ([email protected]) and Daniel Kim
CLIP (Contrastive Language-Image Pre-Training) is a neural network trained on a variety of (image, text) pairs
CLIP [Blog] [Paper] [Model Card] [Colab] CLIP (Contrastive Language-Image Pre-Training) is a neural network trained on a variety of (image, text) pair
The repository includes the code for training cell counting applications. (Keras + Tensorflow)
cell_counting_v2 The repository includes the code for training cell counting applications. (Keras + Tensorflow) Dataset can be downloaded here : http:
Simple keras FCN Encoder/Decoder model for MS-COCO (food subset) segmentation
FCN_MSCOCO_Food_Segmentation Simple keras FCN Encoder/Decoder model for MS-COCO (food subset) segmentation Input data: [http://mscoco.org/dataset/#ove
Wider or Deeper: Revisiting the ResNet Model for Visual Recognition
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
Segmentation Training Pipeline
Segmentation Training Pipeline This package is a part of Musket ML framework. Reasons to use Segmentation Pipeline Segmentation Pipeline was developed
PyTorchMemTracer - Depict GPU memory footprint during DNN training of PyTorch
A Memory Tracer For PyTorch OOM is a nightmare for PyTorch users. However, most
Static Features Classifier - A static features classifier for Point-Could clusters using an Attention-RNN model
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
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.
Code for the paper "Generative design of breakwaters usign deep convolutional neural network as a surrogate model"
Generative design of breakwaters usign deep convolutional neural network as a surrogate model This repository contains the code for the paper "Generat
First steps with Python in Life Sciences
First steps with Python in Life Sciences This course material is part of the "First Steps with Python in Life Science" three-day course of SIB-trainin
To prepare an image processing model to classify the type of disaster based on the image dataset
Disaster Classificiation using CNNs bunnysaini/Disaster-Classificiation Goal To prepare an image processing model to classify the type of disaster bas
Collapse by Conditioning: Training Class-conditional GANs with Limited Data
Collapse by Conditioning: Training Class-conditional GANs with Limited Data Moha
ESGD-M - A stochastic non-convex second order optimizer, suitable for training deep learning models, for PyTorch
ESGD-M - A stochastic non-convex second order optimizer, suitable for training deep learning models, for PyTorch
Pynomial - a lightweight python library for implementing the many confidence intervals for the risk parameter of a binomial model
Pynomial - a lightweight python library for implementing the many confidence intervals for the risk parameter of a binomial model
HistoSeg : Quick attention with multi-loss function for multi-structure segmentation in digital histology images
HistoSeg : Quick attention with multi-loss function for multi-structure segmentation in digital histology images Histological Image Segmentation This
sequitur is a library that lets you create and train an autoencoder for sequential data in just two lines of code
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 is a single vision model for many different visual modalities
Omnivore: A Single Model for Many Visual Modalities [paper][website] OMNIVORE is a single vision model for many different visual modalities. It learns
Cereal box identification in store shelves using computer vision and a single train image per model.
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
Repo for investigation of timeouts that happens with prolonged training on clients
Flower-timeout Repo for investigation of timeouts that happens with prolonged training on clients. This repository is meant purely for demonstration o
GitHub Actions Docker training
GitHub-Actions-Docker-training Training exercise repository for GitHub Actions using a docker base. This repository should be cloned and used for trai
Django Pickled Model
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
Open solution to the Toxic Comment Classification Challenge
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
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
event-driven-model-serving Unified API of Apache Kafka and Google PubSub 1. Proj
This Deep Learning Model Predicts that from which disease you are suffering.
Deep-Learning-Project This Deep Learning Model Predicts that from which disease you are suffering. This Project Covers the Topics of Deep Learning Int
Blackstone is a spaCy model and library for processing long-form, unstructured legal text
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 detectio
Grover is a model for Neural Fake News -- both generation and detection. However, it probably can also be used for other generation tasks.
Original Implementation of Prompt Tuning from Lester, et al, 2021
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
Circuit Training: An open-source framework for generating chip floor plans with distributed deep reinforcement learning
Circuit Training: An open-source framework for generating chip floor plans with distributed deep reinforcement learning. Circuit Training is an open-s
Code for the CVPR2021 workshop paper "Noise Conditional Flow Model for Learning the Super-Resolution Space"
NCSR: Noise Conditional Flow Model for Learning the Super-Resolution Space Official NCSR training PyTorch Code for the CVPR2021 workshop paper "Noise
X-VLM: Multi-Grained Vision Language Pre-Training
X-VLM: learning multi-grained vision language alignments Multi-Grained Vision Language Pre-Training: Aligning Texts with Visual Concepts. Yan Zeng, Xi
Consensus Learning from Heterogeneous Objectives for One-Class Collaborative Filtering
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.
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.
ColossalAI-Examples - Examples of training models with hybrid parallelism using ColossalAI
ColossalAI-Examples This repository contains examples of training models with Co
A novel dual model approach for categorization of unbalanced skin lesion image classes (Presented technical paper 📃)
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)"
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
Finetune the base 64 px GLIDE-text2im model from OpenAI on your own image-text dataset
A handy tool for common machine learning models' hyper-parameter tuning.
Common machine learning models' hyperparameter tuning This repo is for a collection of hyper-parameter tuning for "common" machine learning models, in
A novel Engagement Detection with Multi-Task Training (ED-MTT) system
A novel Engagement Detection with Multi-Task Training (ED-MTT) system which minimizes MSE and triplet loss together to determine the engagement level of students in an e-learning environment.
Python PID Tuner - Makes a model of the System from a Process Reaction Curve and calculates PID Gains
PythonPID_Tuner_SOPDT Step 1: Takes a Process Reaction Curve in csv format - assumes data at 100ms interval (column names CV and PV) Step 2: Makes a r
Caffe-like explicit model constructor. C(onfig)Model
cmodel Caffe-like explicit model constructor. C(onfig)Model Installation pip install git+https://github.com/bonlime/cmodel Usage In order to allow usi
The trained model and denoising example for paper : Cardiopulmonary Auscultation Enhancement with a Two-Stage Noise Cancellation Approach
The trained model and denoising example for paper : Cardiopulmonary Auscultation Enhancement with a Two-Stage Noise Cancellation Approach
TiP-Adapter: Training-free CLIP-Adapter for Better Vision-Language Modeling
TiP-Adapter: Training-free CLIP-Adapter for Better Vision-Language Modeling This is the official code release for the paper 'TiP-Adapter: Training-fre
A PyTorch implementation of VIOLET
VIOLET: End-to-End Video-Language Transformers with Masked Visual-token Modeling A PyTorch implementation of VIOLET Overview VIOLET is an implementati
Official repository for the ICCV 2021 paper: UltraPose: Synthesizing Dense Pose with 1 Billion Points by Human-body Decoupling 3D Model.
UltraPose: Synthesizing Dense Pose with 1 Billion Points by Human-body Decoupling 3D Model Official repository for the ICCV 2021 paper: UltraPose: Syn
A CNN model to detect hand gestures.
Software Used python - programming language used, tested on v3.8 miniconda - for managing virtual environment Libraries Used opencv - pip install open
In this project, we compared Spanish BERT and Multilingual BERT in the Sentiment Analysis task.
Applying BERT Fine Tuning to Sentiment Classification on Amazon Reviews Abstract Sentiment analysis has made great progress in recent years, due to th
Gender Classification Machine Learning Model using Sk-learn in Python with 97%+ accuracy and deployment
Gender-classification This is a ML model to classify Male and Females using some physical characterstics Data. Python Libraries like Pandas,Numpy and
A complete, self-contained example for training ImageNet at state-of-the-art speed with FFCV
ffcv ImageNet Training A minimal, single-file PyTorch ImageNet training script designed for hackability. Run train_imagenet.py to get... ...high accur
Custom IMDB Dataset is extracted between 2020-2021 and custom distilBERT model is trained for movie success probability prediction
IMDB Success Predictor Project involves Web Scraping custom IMDB data between 2020 and 2021 of 10000 movies and shows sorted by number of votes ,fine
SynapseML - an open source library to simplify the creation of scalable machine learning pipelines
Synapse Machine Learning SynapseML (previously MMLSpark) is an open source library to simplify the creation of scalable machine learning pipelines. Sy
Predicting 10 different clothing types using Xception pre-trained model.
Predicting-Clothing-Types Predicting 10 different clothing types using Xception pre-trained model from Keras library. It is reimplemented version from
Scripts used to make and evaluate OpenAlex's concept tagging model
openalex-concept-tagging This repository contains all of the code for getting the concept tagger up and running. To learn more about where this model
The model is designed to train a single and large neural network in order to predict correct translation by reading the given sentence.
Neural Machine Translation communication system The model is basically direct to convert one source language to another targeted language using encode
"Moshpit SGD: Communication-Efficient Decentralized Training on Heterogeneous Unreliable Devices", official implementation
Moshpit SGD: Communication-Efficient Decentralized Training on Heterogeneous Unreliable Devices This repository contains the official PyTorch implemen
BeautyNet is an AI powered model which can tell you whether you're beautiful or not.
BeautyNet BeautyNet is an AI powered model which can tell you whether you're beautiful or not. Download Dataset from here:https://www.kaggle.com/gpios
Deep learning transformer model that generates unique music sequences.
music-ai Deep learning transformer model that generates unique music sequences. Abstract In 2017, a new state-of-the-art was published for natural lan
VGG16 model-based classification project about brain tumor detection.
Brain-Tumor-Classification-with-MRI VGG16 model-based classification project about brain tumor detection. First, you can check what people are doing o
Step by Step on how to create an vision recognition model using LOBE.ai, export the model and run the model in an Azure Function
Step by Step on how to create an vision recognition model using LOBE.ai, export the model and run the model in an Azure Function
Implement of "Training deep neural networks via direct loss minimization" in PyTorch for 0-1 loss
This is the implementation of "Training deep neural networks via direct loss minimization" published at ICML 2016 in PyTorch. The implementation targe
Pianote - An application that helps musicians practice piano ear training
Pianote Pianote is an application that helps musicians practice piano ear traini
🔎 Monitor deep learning model training and hardware usage from your mobile phone 📱
Monitor deep learning model training and hardware usage from mobile. 🔥 Features Monitor running experiments from mobile phone (or laptop) Monitor har
A natural language processing model for sequential sentence classification in medical abstracts.
NLP PubMed Medical Research Paper Abstract (Randomized Controlled Trial) A natural language processing model for sequential sentence classification in
This is a model to classify Vietnamese sign language using Motion history image (MHI) algorithm and CNN.
Vietnamese sign lagnuage recognition using MHI and CNN This is a model to classify Vietnamese sign language using Motion history image (MHI) algorithm
Source code for paper "Black-Box Tuning for Language-Model-as-a-Service"
Black-Box-Tuning Source code for paper "Black-Box Tuning for Language-Model-as-a-Service". Being busy recently, the code in this repo and this tutoria
Compartmental epidemic model to assess undocumented infections: applications to SARS-CoV-2 epidemics in Brazil - Datasets and Codes
Compartmental epidemic model to assess undocumented infections: applications to SARS-CoV-2 epidemics in Brazil - Datasets and Codes The codes for simu
VR Viewport Pose Model for Quantifying and Exploiting Frame Correlations
This repository contains the introduction to the collected VRViewportPose dataset and the code for the IEEE INFOCOM 2022 paper: "VR Viewport Pose Model for Quantifying and Exploiting Frame Correlations"
Code for Reciprocal Adversarial Learning for Brain Tumor Segmentation: A Solution to BraTS Challenge 2021 Segmentation Task
BRATS 2021 Solution For Segmentation Task This repo contains the supported pytorch code and configuration files to reproduce 3D medical image segmenta
This repo generates the training data and the model for Morpheus-Deblend
Morpheus-Deblend This repo generates the training data and the model for Morpheus-Deblend. This is the active development repo for the project and as
Jingju baseline - A baseline model of our project of Beijing opera script generation
Jingju Baseline It is a baseline of our project about Beijing opera script gener
Sentinel-1 vessel detection model used in the xView3 challenge
sar_vessel_detect Code for the AI2 Skylight team's submission in the xView3 competition (https://iuu.xview.us) for vessel detection in Sentinel-1 SAR
Using Global fishing watch's data to build a machine learning model that can identify illegal fishing and poaching activities through satellite and geo-location data.
Using Global fishing watch's data to build a machine learning model that can identify illegal fishing and poaching activities through satellite and geo-location data.
From Perceptron model to Deep Neural Network from scratch in Python.
Neural-Network-Basics Aim of this Repository: From Perceptron model to Deep Neural Network (from scratch) in Python. ** Currently working on a basic N
Book Recommender System Using Sci-kit learn N-neighbours
Model-Based-Recommender-Engine I created a book Recommender System using Sci-kit learn's N-neighbours algorithm for my model and the streamlit library
The code for our paper Semi-Supervised Learning with Multi-Head Co-Training
Semi-Supervised Learning with Multi-Head Co-Training (PyTorch) Abstract Co-training, extended from self-training, is one of the frameworks for semi-su
Madanalysis5 - A package for event file analysis and recasting of LHC results
Welcome to MadAnalysis 5 Outline What is MadAnalysis 5? Requirements Downloading
Code for the paper 'A High Performance CRF Model for Clothes Parsing'.
Clothes Parsing Overview This code provides an implementation of the research paper: A High Performance CRF Model for Clothes Parsing Edgar Simo-S
Explores the python bytecode, provides some tools to access it for fun and profit.
Pyasmtools - looking at the python bytecode for fun and profit. The pyasmtools library is made up of two parts A python bytecode disassembler . See Py