2506 Repositories
Python Model-Training-as-a-CI-CD-System Libraries
Python scripts form performing stereo depth estimation using the high res stereo model in PyTorch .
PyTorch-High-Res-Stereo-Depth-Estimation Python scripts form performing stereo depth estimation using the high res stereo model in PyTorch. Stereo dep
Python scripts form performing stereo depth estimation using the CoEx model in ONNX.
ONNX-CoEx-Stereo-Depth-estimation Python scripts form performing stereo depth estimation using the CoEx model in ONNX. Stereo depth estimation on the
Model Quantization Benchmark
MQBench Update V0.0.2 Fix academic prepare setting. More deployable prepare process. Fix setup.py. Fix deploy on SNPE. Fix convert_deploy bug. Add Qua
Code and checkpoints for training the transformer-based Table QA models introduced in the paper TAPAS: Weakly Supervised Table Parsing via Pre-training.
End-to-end neural table-text understanding models.
Bridging Vision and Language Model
BriVL BriVL (Bridging Vision and Language Model) 是首个中文通用图文多模态大规模预训练模型。BriVL模型在图文检索任务上有着优异的效果,超过了同期其他常见的多模态预训练模型(例如UNITER、CLIP)。 BriVL论文:WenLan: Bridgi
Pathdreamer: A World Model for Indoor Navigation
Pathdreamer: A World Model for Indoor Navigation This repository hosts the open source code for Pathdreamer, to be presented at ICCV 2021. Paper | Pro
Example scripts for the detection of lanes using the ultra fast lane detection model in Tensorflow Lite.
TFlite Ultra Fast Lane Detection Inference Example scripts for the detection of lanes using the ultra fast lane detection model in Tensorflow Lite. So
Generate text line images for training deep learning OCR model (e.g. CRNN)
Generate text line images for training deep learning OCR model (e.g. CRNN)
Waydroid is a container-based approach to boot a full Android system on a regular GNU/Linux system like Ubuntu.
Waydroid is a container-based approach to boot a full Android system on a regular GNU/Linux system like Ubuntu.
Demonstration of the Model Training as a CI/CD System in Vertex AI
Model Training as a CI/CD System This project demonstrates the machine model training as a CI/CD system in GCP platform. You will see more detailed wo
QRec: A Python Framework for quick implementation of recommender systems (TensorFlow Based)
QRec is a Python framework for recommender systems (Supported by Python 3.7.4 and Tensorflow 1.14+) in which a number of influential and newly state-of-the-art recommendation models are implemented. QRec has a lightweight architecture and provides user-friendly interfaces. It can facilitate model implementation and evaluation.
Codes for CIKM'21 paper 'Self-Supervised Graph Co-Training for Session-based Recommendation'.
COTREC Codes for CIKM'21 paper 'Self-Supervised Graph Co-Training for Session-based Recommendation'. Requirements: Python 3.7, Pytorch 1.6.0 Best Hype
🔐 Login & Register System
🔐 Login & Register System This is a developable login and register system. Enter your username and password to register or login to account. Automati
MWPToolkit is a PyTorch-based toolkit for Math Word Problem (MWP) solving.
MWPToolkit is a PyTorch-based toolkit for Math Word Problem (MWP) solving. It is a comprehensive framework for research purpose that integrates popular MWP benchmark datasets and typical deep learning-based MWP algorithms.
Train GPT-3 model on V100(16GB Mem) Using improved Transformer.
GPT-X using transformer pytorch
Python scripts for performing stereo depth estimation using the HITNET Tensorflow model.
HITNET-Stereo-Depth-estimation Python scripts for performing stereo depth estimation using the HITNET Tensorflow model from Google Research. Stereo de
Collection of NLP model explanations and accompanying analysis tools
Thermostat is a large collection of NLP model explanations and accompanying analysis tools. Combines explainability methods from the captum library wi
Simple linear model implementations from scratch.
Hand Crafted Models Simple linear model implementations from scratch. Table of contents Overview Project Structure Getting started Citing this project
This repo uses a combination of logits and feature distillation method to teach the PSPNet model of ResNet18 backbone with the PSPNet model of ResNet50 backbone. All the models are trained and tested on the PASCAL-VOC2012 dataset.
PSPNet-logits and feature-distillation Introduction This repository is based on PSPNet and modified from semseg and Pixelwise_Knowledge_Distillation_P
🍅🍅🍅YOLOv5-Lite: lighter, faster and easier to deploy. Evolved from yolov5 and the size of model is only 1.7M (int8) and 3.3M (fp16). It can reach 10+ FPS on the Raspberry Pi 4B when the input size is 320×320~
YOLOv5-Lite:lighter, faster and easier to deploy Perform a series of ablation experiments on yolov5 to make it lighter (smaller Flops, lower memory, a
A Pytree Module system for Deep Learning in JAX
Treex A Pytree-based Module system for Deep Learning in JAX Intuitive: Modules are simple Python objects that respect Object-Oriented semantics and sh
machine learning model deployment project of Iris classification model in a minimal UI using flask web framework and deployed it in Azure cloud using Azure app service
This is a machine learning model deployment project of Iris classification model in a minimal UI using flask web framework and deployed it in Azure cloud using Azure app service. We initially made this project as a requirement for an internship at Indian Servers. We are now making it open to contribution.
VIL-100: A New Dataset and A Baseline Model for Video Instance Lane Detection (ICCV 2021)
Preparation Please see dataset/README.md to get more details about our datasets-VIL100 Please see INSTALL.md to install environment and evaluation too
TAPEX: Table Pre-training via Learning a Neural SQL Executor
TAPEX: Table Pre-training via Learning a Neural SQL Executor The official repository which contains the code and pre-trained models for our paper TAPE
CAPRI: Context-Aware Interpretable Point-of-Interest Recommendation Framework
CAPRI: Context-Aware Interpretable Point-of-Interest Recommendation Framework This repository contains a framework for Recommender Systems (RecSys), a
The system to host your files on the Discord application
Distorage The system to host your files on the Discord application Documentation Documentation Distorage How to use the package You can install it wit
Voice of Pajlada with model and weights.
Pajlada TTS Stripped down version of ForwardTacotron (https://github.com/as-ideas/ForwardTacotron) with pretrained weights for Pajlada's (https://gith
System monitor - A python-based real-time system monitoring tool
System monitor A python-based real-time system monitoring tool Screenshots Installation Run My project with these commands pip install -r requiremen
Konomi: Kind and Optimized Next brOadcast watching systeM Infrastructure
Konomi 備考・注意事項 現在 α 版で、まだ実験的なプロダクトです。通常利用には耐えないでしょうし、サポートもできません。 安定しているとは到底言いがたい品質ですが、それでも構わない方のみ導入してください。 使い方などの説明も用意できていないため、自力でトラブルに対処できるエンジニアの方以外に
An original implementation of "Noisy Channel Language Model Prompting for Few-Shot Text Classification"
Channel LM Prompting (and beyond) This includes an original implementation of Sewon Min, Mike Lewis, Hannaneh Hajishirzi, Luke Zettlemoyer. "Noisy Cha
Ongoing research training transformer language models at scale, including: BERT & GPT-2
Megatron (1 and 2) is a large, powerful transformer developed by the Applied Deep Learning Research team at NVIDIA.
Example scripts for the detection of lanes using the ultra fast lane detection model in ONNX.
Example scripts for the detection of lanes using the ultra fast lane detection model in ONNX.
The Official Implementation of the ICCV-2021 Paper: Semantically Coherent Out-of-Distribution Detection.
SCOOD-UDG (ICCV 2021) This repository is the official implementation of the paper: Semantically Coherent Out-of-Distribution Detection Jingkang Yang,
The official implementation of the Interspeech 2021 paper WSRGlow: A Glow-based Waveform Generative Model for Audio Super-Resolution.
WSRGlow The official implementation of the Interspeech 2021 paper WSRGlow: A Glow-based Waveform Generative Model for Audio Super-Resolution. Audio sa
CrossNorm and SelfNorm for Generalization under Distribution Shifts (ICCV 2021)
CrossNorm (CN) and SelfNorm (SN) (Accepted at ICCV 2021) This is the official PyTorch implementation of our CNSN paper, in which we propose CrossNorm
【ACMMM 2021】DSANet: Dynamic Segment Aggregation Network for Video-Level Representation Learning
DSANet: Dynamic Segment Aggregation Network for Video-Level Representation Learning (ACMMM 2021) Overview We release the code of the DSANet (Dynamic S
CrossNorm and SelfNorm for Generalization under Distribution Shifts (ICCV 2021)
CrossNorm (CN) and SelfNorm (SN) (Accepted at ICCV 2021) This is the official PyTorch implementation of our CNSN paper, in which we propose CrossNorm
A pytorch implementation of Paper "Improved Training of Wasserstein GANs"
WGAN-GP An pytorch implementation of Paper "Improved Training of Wasserstein GANs". Prerequisites Python, NumPy, SciPy, Matplotlib A recent NVIDIA GPU
Code used to generate the results appearing in "Train longer, generalize better: closing the generalization gap in large batch training of neural networks"
Train longer, generalize better - Big batch training This is a code repository used to generate the results appearing in "Train longer, generalize bet
Transfer Learning Shootout for PyTorch's model zoo (torchvision)
pytorch-retraining Transfer Learning shootout for PyTorch's model zoo (torchvision). Load any pretrained model with custom final layer (num_classes) f
Accelerate Neural Net Training by Progressively Freezing Layers
FreezeOut A simple technique to accelerate neural net training by progressively freezing layers. This repository contains code for the extended abstra
Pytorch implementation of "Forward Thinking: Building and Training Neural Networks One Layer at a Time"
forward-thinking-pytorch Pytorch implementation of Forward Thinking: Building and Training Neural Networks One Layer at a Time Requirements Python 2.7
A PyTorch implementation of the Transformer model in "Attention is All You Need".
Attention is all you need: A Pytorch Implementation This is a PyTorch implementation of the Transformer model in "Attention is All You Need" (Ashish V
PyTorch implementation of SampleRNN: An Unconditional End-to-End Neural Audio Generation Model
samplernn-pytorch A PyTorch implementation of SampleRNN: An Unconditional End-to-End Neural Audio Generation Model. It's based on the reference implem
PyTorch implementation of the supervised learning experiments from the paper Model-Agnostic Meta-Learning (MAML)
pytorch-maml This is a PyTorch implementation of the supervised learning experiments from the paper Model-Agnostic Meta-Learning (MAML): https://arxiv
PyTorch implementation of Tacotron speech synthesis model.
tacotron_pytorch PyTorch implementation of Tacotron speech synthesis model. Inspired from keithito/tacotron. Currently not as much good speech quality
Unofficial Alias-Free GAN implementation. Based on rosinality's version with expanded training and inference options.
Alias-Free GAN An unofficial version of Alias-Free Generative Adversarial Networks (https://arxiv.org/abs/2106.12423). This repository was heavily bas
Evidence enables analysts to deliver a polished business intelligence system using SQL and markdown.
Evidence enables analysts to deliver a polished business intelligence system using SQL and markdown
Implementation of Token Shift GPT - An autoregressive model that solely relies on shifting the sequence space for mixing
Token Shift GPT Implementation of Token Shift GPT - An autoregressive model that relies solely on shifting along the sequence dimension and feedforwar
Script to use SysWhispers2 direct system calls from Cobalt Strike BOFs
SysWhispers2BOF Script to use SysWhispers2 direct system calls from Cobalt Strike BOFs. Introduction This script was initially created to fix specific
gitfs is a FUSE file system that fully integrates with git - Version controlled file system
gitfs is a FUSE file system that fully integrates with git. You can mount a remote repository's branch locally, and any subsequent changes made to the files will be automatically committed to the remote.
A Survey of Natural Language Generation in Task-Oriented Dialogue System (TOD): Recent Advances and New Frontiers
A Survey of Natural Language Generation in Task-Oriented Dialogue System (TOD): Recent Advances and New Frontiers
[Preprint] "Bag of Tricks for Training Deeper Graph Neural Networks A Comprehensive Benchmark Study" by Tianlong Chen*, Kaixiong Zhou*, Keyu Duan, Wenqing Zheng, Peihao Wang, Xia Hu, Zhangyang Wang
Bag of Tricks for Training Deeper Graph Neural Networks: A Comprehensive Benchmark Study Codes for [Preprint] Bag of Tricks for Training Deeper Graph
Experiments on Flood Segmentation on Sentinel-1 SAR Imagery with Cyclical Pseudo Labeling and Noisy Student Training
Flood Detection Challenge This repository contains code for our submission to the ETCI 2021 Competition on Flood Detection (Winning Solution #2). Acco
ST++: Make Self-training Work Better for Semi-supervised Semantic Segmentation
ST++ This is the official PyTorch implementation of our paper: ST++: Make Self-training Work Better for Semi-supervised Semantic Segmentation. Lihe Ya
We present a framework for training multi-modal deep learning models on unlabelled video data by forcing the network to learn invariances to transformations applied to both the audio and video streams.
Multi-Modal Self-Supervision using GDT and StiCa This is an official pytorch implementation of papers: Multi-modal Self-Supervision from Generalized D
Empower Sequence Labeling with Task-Aware Language Model
LM-LSTM-CRF Check Our New NER Toolkit 🚀 🚀 🚀 Inference: LightNER: inference w. models pre-trained / trained w. any following tools, efficiently. Tra
PyTorch DepthNet Training on Still Box dataset
DepthNet training on Still Box Project page This code can replicate the results of our paper that was published in UAVg-17. If you use this repo in yo
Evaluation suite for large-scale language models.
This repo contains code for running the evaluations and reproducing the results from the Jurassic-1 Technical Paper (see blog post), with current support for running the tasks through both the AI21 Studio API and OpenAI's GPT3 API.
Transformer model implemented with Pytorch
transformer-pytorch Transformer model implemented with Pytorch Attention is all you need-[Paper] Architecture Self-Attention self_attention.py class
A management system designed for the employees of MIRAS (Art Gallery). It is used to sell/cancel tickets, book/cancel events and keeps track of all upcoming events.
Art-Galleria-Management-System Its a management system designed for the employees of MIRAS (Art Gallery). Backend : Python Frontend : Django Database
WinBoost: Boost your windows system.
Winboost runs a complete checkup of your entire system locating junk files, speed-reducing issues and causes of any system or application glitches or crashes. Through a lot of research and testing, we have worked out precise techniques that allow locating issues, which can be safely removed with no risk of damaging your operating system.
Official implementation of the ICCV 2021 paper "Conditional DETR for Fast Training Convergence".
The DETR approach applies the transformer encoder and decoder architecture to object detection and achieves promising performance. In this paper, we handle the critical issue, slow training convergence, and present a conditional cross-attention mechanism for fast DETR training. Our approach is motivated by that the cross-attention in DETR relies highly on the content embeddings and that the spatial embeddings make minor contributions, increasing the need for high-quality content embeddings and thus increasing the training difficulty.
Dynamic Divide-and-Conquer Adversarial Training for Robust Semantic Segmentation (ICCV2021)
Dynamic Divide-and-Conquer Adversarial Training for Robust Semantic Segmentation This is a pytorch project for the paper Dynamic Divide-and-Conquer Ad
Convert Apple NeuralHash model for CSAM Detection to ONNX.
Apple NeuralHash is a perceptual hashing method for images based on neural networks. It can tolerate image resize and compression.
In this project we investigate the performance of the SetCon model on realistic video footage. Therefore, we implemented the model in PyTorch and tested the model on two example videos.
Contrastive Learning of Object Representations Supervisor: Prof. Dr. Gemma Roig Institutions: Goethe University CVAI - Computational Vision & Artifici
Customizable RecSys Simulator for OpenAI Gym
gym-recsys: Customizable RecSys Simulator for OpenAI Gym Installation | How to use | Examples | Citation This package describes an OpenAI Gym interfac
LONG-TERM SERIES FORECASTING WITH QUERYSELECTOR – EFFICIENT MODEL OF SPARSEATTENTION
Query Selector Here you can find code and data loaders for the paper https://arxiv.org/pdf/2107.08687v1.pdf . Query Selector is a novel approach to sp
Code for EmBERT, a transformer model for embodied, language-guided visual task completion.
Code for EmBERT, a transformer model for embodied, language-guided visual task completion.
The tl;dr on a few notable transformer/language model papers + other papers (alignment, memorization, etc).
The tl;dr on a few notable transformer/language model papers + other papers (alignment, memorization, etc).
Learn meanings behind words is a key element in NLP. This project concentrates on the disambiguation of preposition senses. Therefore, we train a bert-transformer model and surpass the state-of-the-art.
New State-of-the-Art in Preposition Sense Disambiguation Supervisor: Prof. Dr. Alexander Mehler Alexander Henlein Institutions: Goethe University TTLa
😇A pyTorch implementation of the DeepMoji model: state-of-the-art deep learning model for analyzing sentiment, emotion, sarcasm etc
------ Update September 2018 ------ It's been a year since TorchMoji and DeepMoji were released. We're trying to understand how it's being used such t
Unofficial pytorch implementation for Self-critical Sequence Training for Image Captioning. and others.
An Image Captioning codebase This is a codebase for image captioning research. It supports: Self critical training from Self-critical Sequence Trainin
IAST: Instance Adaptive Self-training for Unsupervised Domain Adaptation (ECCV 2020)
This repo is the official implementation of our paper "Instance Adaptive Self-training for Unsupervised Domain Adaptation". The purpose of this repo is to better communicate with you and respond to your questions. This repo is almost the same with Another-Version, and you can also refer to that version.
Learning and Building Convolutional Neural Networks using PyTorch
Image Classification Using Deep Learning Learning and Building Convolutional Neural Networks using PyTorch. Models, selected are based on number of ci
Ongoing research training transformer language models at scale, including: BERT & GPT-2
What is this fork of Megatron-LM and Megatron-DeepSpeed This is a detached fork of https://github.com/microsoft/Megatron-DeepSpeed, which in itself is
CLI helper to install Github releases on your system.
gh-release-install is a CLI helper to install Github releases on your system. It can be used for pretty much anything, to install a formatter in your CI, deploy some binary using an orcherstration tool, or on your desktop.
We evaluate our method on different datasets (including ShapeNet, CUB-200-2011, and Pascal3D+) and achieve state-of-the-art results, outperforming all the other supervised and unsupervised methods and 3D representations, all in terms of performance, accuracy, and training time.
An Effective Loss Function for Generating 3D Models from Single 2D Image without Rendering Papers with code | Paper Nikola Zubić Pietro Lio University
FedScale: Benchmarking Model and System Performance of Federated Learning
FedScale: Benchmarking Model and System Performance of Federated Learning (Paper) This repository contains scripts and instructions of building FedSca
SlotRefine: A Fast Non-Autoregressive Model forJoint Intent Detection and Slot Filling
SlotRefine: A Fast Non-Autoregressive Model for Joint Intent Detection and Slot Filling Reference Main paper to be cited (Di Wu et al., 2020) @article
A DNN inference latency prediction toolkit for accurately modeling and predicting the latency on diverse edge devices.
Note: This is an alpha (preview) version which is still under refining. nn-Meter is a novel and efficient system to accurately predict the inference l
Code for EmBERT, a transformer model for embodied, language-guided visual task completion.
Code for EmBERT, a transformer model for embodied, language-guided visual task completion.
(CVPR2021) Kaleido-BERT: Vision-Language Pre-training on Fashion Domain
Kaleido-BERT: Vision-Language Pre-training on Fashion Domain Mingchen Zhuge*, Dehong Gao*, Deng-Ping Fan#, Linbo Jin, Ben Chen, Haoming Zhou, Minghui
Code of PVTv2 is released! PVTv2 largely improves PVTv1 and works better than Swin Transformer with ImageNet-1K pre-training.
Updates (2020/06/21) Code of PVTv2 is released! PVTv2 largely improves PVTv1 and works better than Swin Transformer with ImageNet-1K pre-training. Pyr
The RWKV Language Model
RWKV-LM We propose the RWKV language model, with alternating time-mix and channel-mix layers: The R, K, V are generated by linear transforms of input,
AutoVideo: An Automated Video Action Recognition System
AutoVideo is a system for automated video analysis. It is developed based on D3M infrastructure, which describes machine learning with generic pipeline languages. Currently, it focuses on video action recognition, supporting various state-of-the-art video action recognition algorithms. It also supports automated model selection and hyperparameter tuning. AutoVideo is developed by DATA Lab at Texas A&M University.
LightSeq is a high performance training and inference library for sequence processing and generation implemented in CUDA
LightSeq: A High Performance Library for Sequence Processing and Generation
How to Become More Salient? Surfacing Representation Biases of the Saliency Prediction Model
How to Become More Salient? Surfacing Representation Biases of the Saliency Prediction Model
nn-Meter is a novel and efficient system to accurately predict the inference latency of DNN models on diverse edge devices
A DNN inference latency prediction toolkit for accurately modeling and predicting the latency on diverse edge devices.
End-to-end text to speech system using gruut and onnx. There are 40 voices available across 8 languages.
End to end text to speech system using gruut and onnx
This is the pytorch implementation for the paper: *Learning Accurate Performance Predictors for Ultrafast Automated Model Compression*, which is in submission to TPAMI
SeerNet This is the pytorch implementation for the paper: Learning Accurate Performance Predictors for Ultrafast Automated Model Compression, which is
A Serverless Application Model stack that persists the $XRP price to the XRPL every minute as a TrustLine. There are no servers, it is effectively a "smart contract" in Python for the XRPL.
xrpl-price-persist-oracle-sam This is a XRPL Oracle that publishes external data into the XRPL. This Oracle was inspired by XRPL-Labs/XRPL-Persist-Pri
Emotional conditioned music generation using transformer-based model.
This is the official repository of EMOPIA: A Multi-Modal Pop Piano Dataset For Emotion Recognition and Emotion-based Music Generation. The paper has b
The Adapter-Bot: All-In-One Controllable Conversational Model
The Adapter-Bot: All-In-One Controllable Conversational Model This is the implementation of the paper: The Adapter-Bot: All-In-One Controllable Conver
MQBench: Towards Reproducible and Deployable Model Quantization Benchmark
MQBench: Towards Reproducible and Deployable Model Quantization Benchmark We propose a benchmark to evaluate different quantization algorithms on vari
Partial implementation of ODE-GAN technique from the paper Training Generative Adversarial Networks by Solving Ordinary Differential Equations
ODE GAN (Prototype) in PyTorch Partial implementation of ODE-GAN technique from the paper Training Generative Adversarial Networks by Solving Ordinary
Implementation of the paper: "SinGAN: Learning a Generative Model from a Single Natural Image"
SinGAN This is an unofficial implementation of SinGAN from someone who's been sitting right next to SinGAN's creator for almost five years. Please ref
Simple two factor authemtication system, made by me.
Simple two factor authemtication system, made by me. Honestly, i don't even know How 2FAs work I just used my knowledge and did whatever i could. Send
open-information-extraction-system, build open-knowledge-graph(SPO, subject-predicate-object) by pyltp(version==3.4.0)
中文开放信息抽取系统, open-information-extraction-system, build open-knowledge-graph(SPO, subject-predicate-object) by pyltp(version==3.4.0)
Image enhancing model for making a blurred image to be somehow clearer than before
This is a very small prject which helps in enhancing the images by taking a Input images. This project has many features like detcting the faces and enhaning the faces itself and also a feature which enhances the whole image