134 Repositories
Python yas-train Libraries
How to train a CNN to 99% accuracy on MNIST in less than a second on a laptop
Training a NN to 99% accuracy on MNIST in 0.76 seconds A quick study on how fast you can reach 99% accuracy on MNIST with a single laptop. Our answer
StorSeismic: An approach to pre-train a neural network to store seismic data features
StorSeismic: An approach to pre-train a neural network to store seismic data features This repository contains codes and resources to reproduce experi
In this tutorial, you will perform inference across 10 well-known pre-trained object detectors and fine-tune on a custom dataset. Design and train your own object detector.
Object Detection Object detection is a computer vision task for locating instances of predefined objects in images or videos. In this tutorial, you wi
Train CNNs for the fruits360 data set in NTOU CS「Machine Vision」class.
CNNs fruits360 Train CNNs for the fruits360 data set in NTOU CS「Machine Vision」class. CNN on a pretrained model Build a CNN on a pretrained model, Res
[CVPR 2022] Official code for the paper: "A Stitch in Time Saves Nine: A Train-Time Regularizing Loss for Improved Neural Network Calibration"
MDCA Calibration This is the official PyTorch implementation for the paper: "A Stitch in Time Saves Nine: A Train-Time Regularizing Loss for Improved
Application to help find best train itinerary, uses speech to text, has a spam filter to segregate invalid inputs, NLP and Pathfinding algos.
T-IAI-901-MSC2022 - GROUP 18 Gestion de projet Notre travail a été organisé et réparti dans un Trello. https://trello.com/b/X3s2fpPJ/ia-projet Install
This repo contains the code required to train the multivariate time-series Transformer.
Multi-Variate Time-Series Transformer This repo contains the code required to train the multivariate time-series Transformer. Download the data The No
Dicionario-git-github - Dictionary created to help train new users of Git and GitHub applications
Dicionário 📕 Dicionário criado com o objetivo de auxiliar no treinamento de nov
Simple flask api. Countdown to next train for each station in the subway system.
Simple flask api. Countdown to next train for each station in the subway system.
Self-supervised learning algorithms provide a way to train Deep Neural Networks in an unsupervised way using contrastive losses
Self-supervised learning Self-supervised learning algorithms provide a way to train Deep Neural Networks in an unsupervised way using contrastive loss
NaturalCC is a sequence modeling toolkit that allows researchers and developers to train custom models
NaturalCC NaturalCC is a sequence modeling toolkit that allows researchers and developers to train custom models for many software engineering tasks,
A beginner’s guide to train and deploy machine learning pipelines in Python using PyCaret
This model involves Insurance bill prediction, which was subsequently deployed on Heroku PaaS
This repository contains code to train and render Mixture of Volumetric Primitives (MVP) models
Mixture of Volumetric Primitives -- Training and Evaluation This repository contains code to train and render Mixture of Volumetric Primitives (MVP) m
Use AutoModelForSeq2SeqLM in Huggingface Transformers to train COMET
Training COMET using seq2seq setting Use AutoModelForSeq2SeqLM in Huggingface Transformers to train COMET. The codes are modified from run_summarizati
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
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
A repo to show how to use custom dataset to train s2anet, and change backbone to resnext101
A repo to show how to use custom dataset to train s2anet, and change backbone to resnext101
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
Meta learning algorithms to train cross-lingual NLI (multi-task) models
Meta learning algorithms to train cross-lingual NLI (multi-task) models
This is a good project to train your logic game with python language
JO-KEN-PÔ!!! | Description | basic. I make this game only to train. This is a good project to train your logic game with python language. This game is
Files for a tutorial to train SegNet for road scenes using the CamVid dataset
SegNet and Bayesian SegNet Tutorial This repository contains all the files for you to complete the 'Getting Started with SegNet' and the 'Bayesian Seg
Project dự đoán giá cổ phiếu bằng thuật toán LSTM gồm: code train và code demo
Web predicts stock prices using Long - Short Term Memory algorithm Give me some start please!!! User interface image: Choose: DayBegin, DayEnd, Stock
This repository is a basic Machine Learning train & validation Template (Using PyTorch)
pytorch_ml_template This repository is a basic Machine Learning train & validation Template (Using PyTorch) TODO Markdown 사용법 Build Docker 사용법 Anacond
Use stochastic processes to generate samples and use them to train a fully-connected neural network based on Keras
Use stochastic processes to generate samples and use them to train a fully-connected neural network based on Keras which will then be used to generate residuals
Train Yolov4 using NBX-Jobs
yolov4-trainer-nbox Train Yolov4 using NBX-Jobs. Use the powerfull functionality available in nbox-SDK repo to train a tiny-Yolo v4 model on Pascal VO
A Simulation Environment to train Robots in Large Realistic Interactive Scenes
iGibson: A Simulation Environment to train Robots in Large Realistic Interactive Scenes iGibson is a simulation environment providing fast visual rend
Train Scene Graph Generation for Visual Genome and GQA in PyTorch = 1.2 with improved zero and few-shot generalization.
Scene Graph Generation Object Detections Ground truth Scene Graph Generated Scene Graph In this visualization, woman sitting on rock is a zero-shot tr
Do you like Quick, Draw? Well what if you could train/predict doodles drawn inside Streamlit? Also draws lines, circles and boxes over background images for annotation.
Streamlit - Drawable Canvas Streamlit component which provides a sketching canvas using Fabric.js. Features Draw freely, lines, circles, boxes and pol
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
Learning to Self-Train for Semi-Supervised Few-Shot
Learning to Self-Train for Semi-Supervised Few-Shot Classification This repository contains the TensorFlow implementation for NeurIPS 2019 Paper "Lear
An implementation of the Contrast Predictive Coding (CPC) method to train audio features in an unsupervised fashion.
CPC_audio This code implements the Contrast Predictive Coding algorithm on audio data, as described in the paper Unsupervised Pretraining Transfers we
EmoTag helps you train emotion detection model for Chinese audios
emoTag emoTag helps you train emotion detection model for Chinese audios. Environment pip install -r requirement.txt Data We used Emotional Speech Dat
PyTorch implementation of Train Short, Test Long: Attention with Linear Biases Enables Input Length Extrapolation.
ALiBi PyTorch implementation of Train Short, Test Long: Attention with Linear Biases Enables Input Length Extrapolation. Quickstart Clone this reposit
Train BPE with fastBPE, and load to Huggingface Tokenizer.
BPEer Train BPE with fastBPE, and load to Huggingface Tokenizer. Description The BPETrainer of Huggingface consumes a lot of memory when I am training
TerminalGV is a very simple client to display stats about your SNCF TGV/TER train in your terminal.
TerminalGV So I got bored in the train, TerminalGV is a very simple client to display stats about your SNCF TGV/TER train in your terminal. The "on-tr
This repository contains the code needed to train Mega-NeRF models and generate the sparse voxel octrees
Mega-NeRF This repository contains the code needed to train Mega-NeRF models and generate the sparse voxel octrees used by the Mega-NeRF-Dynamic viewe
Train emoji embeddings based on emoji descriptions.
emoji2vec This is my attempt to train, visualize and evaluate emoji embeddings as presented by Ben Eisner, Tim Rocktäschel, Isabelle Augenstein, Matko
PyG (PyTorch Geometric) - A library built upon PyTorch to easily write and train Graph Neural Networks (GNNs)
PyG (PyTorch Geometric) is a library built upon PyTorch to easily write and train Graph Neural Networks (GNNs) for a wide range of applications related to structured data.
Codes to pre-train T5 (Text-to-Text Transfer Transformer) models pre-trained on Japanese web texts
t5-japanese Codes to pre-train T5 (Text-to-Text Transfer Transformer) models pre-trained on Japanese web texts. The following is a list of models that
Music Source Separation; Train & Eval & Inference piplines and pretrained models we used for 2021 ISMIR MDX Challenge.
Introduction 1. Usage (For MSS) 1.1 Prepare running environment 1.2 Use pretrained model 1.3 Train new MSS models from scratch 1.3.1 How to train 1.3.
Train custom VR face tracking parameters
Pal Buddy Guy: The anipal's best friend This is a small script to improve upon the tracking capabilities of the Vive Pro Eye and facial tracker. You c
Reproduction of Vision Transformer in Tensorflow2. Train from scratch and Finetune.
Vision Transformer(ViT) in Tensorflow2 Tensorflow2 implementation of the Vision Transformer(ViT). This repository is for An image is worth 16x16 words
Train and use generative text models in a few lines of code.
blather Train and use generative text models in a few lines of code. To see blather in action check out the colab notebook! Installation Use the packa
Yas CRNN model training - Yet Another Genshin Impact Scanner
Yas-Train Yet Another Genshin Impact Scanner 又一个原神圣遗物导出器 介绍 该仓库为 Yas 的模型训练程序 相关资料 MobileNetV3 CRNN 使用 假设你会设置基本的pytorch环境。 生成数据集 python main.py gen 训练
The repo contains the code to train and evaluate a system which extracts relations and explanations from dialogue.
The repo contains the code to train and evaluate a system which extracts relations and explanations from dialogue. How do I cite D-REX? For now, cite
Train neural network for semantic segmentation (deep lab V3) with pytorch in less then 50 lines of code
Train neural network for semantic segmentation (deep lab V3) with pytorch in 50 lines of code Train net semantic segmentation net using Trans10K datas
Train Dense Passage Retriever (DPR) with a single GPU
Gradient Cached Dense Passage Retrieval Gradient Cached Dense Passage Retrieval (GC-DPR) - is an extension of the original DPR library. We introduce G
Research code for "What to Pre-Train on? Efficient Intermediate Task Selection", EMNLP 2021
efficient-task-transfer This repository contains code for the experiments in our paper "What to Pre-Train on? Efficient Intermediate Task Selection".
EMNLP 2021 paper "Pre-train or Annotate? Domain Adaptation with a Constrained Budget".
Pre-train or Annotate? Domain Adaptation with a Constrained Budget This repo contains code and data associated with EMNLP 2021 paper "Pre-train or Ann
Train the HRNet model on ImageNet
High-resolution networks (HRNets) for Image classification News [2021/01/20] Add some stronger ImageNet pretrained models, e.g., the HRNet_W48_C_ssld_
This is the face keypoint train code of project face-detection-project
face-key-point-pytorch 1. Data structure The structure of landmarks_jpg is like below: |--landmarks_jpg |----AFW |------AFW_134212_1_0.jpg |------AFW_
Train an imgs.ai model on your own dataset
imgs.ai is a fast, dataset-agnostic, deep visual search engine for digital art history based on neural network embeddings.
Simple command line tool to train and deploy your machine learning models with AWS SageMaker
metamaker Simple command line tool to train and deploy your machine learning models with AWS SageMaker Features metamaker enables you to: Build a dock
This repository provides an unified frameworks to train and test the state-of-the-art few-shot font generation (FFG) models.
FFG-benchmarks This repository provides an unified frameworks to train and test the state-of-the-art few-shot font generation (FFG) models. What is Fe
HuggingTweets - Train a model to generate tweets
HuggingTweets - Train a model to generate tweets Create in 5 minutes a tweet generator based on your favorite Tweeter Make my own model with the demo
Train SN-GAN with AdaBelief
SNGAN-AdaBelief Train a state-of-the-art spectral normalization GAN with AdaBelief https://github.com/juntang-zhuang/Adabelief-Optimizer Acknowledgeme
NVTabular is a feature engineering and preprocessing library for tabular data designed to quickly and easily manipulate terabyte scale datasets used to train deep learning based recommender systems.
NVTabular is a feature engineering and preprocessing library for tabular data designed to quickly and easily manipulate terabyte scale datasets used to train deep learning based recommender systems.
Python script for diving image data to train test and val
dataset-division-to-train-val-test-python python script for dividing image data to train test and val If you have an image dataset in the following st
A library that integrates huggingface transformers with the world of fastai, giving fastai devs everything they need to train, evaluate, and deploy transformer specific models.
blurr A library that integrates huggingface transformers with version 2 of the fastai framework Install You can now pip install blurr via pip install
apricot implements submodular optimization for the purpose of selecting subsets of massive data sets to train machine learning models quickly.
Please consider citing the manuscript if you use apricot in your academic work! You can find more thorough documentation here. apricot implements subm
This toolkit provides codes to download and pre-process the SLUE datasets, train the baseline models, and evaluate SLUE tasks.
slue-toolkit We introduce Spoken Language Understanding Evaluation (SLUE) benchmark. This toolkit provides codes to download and pre-process the SLUE
Record railway train route profile with GNSS tools
Train route profile recording with GNSS technology based on ARDUINO platform Project target Develop GNSS recording tools based on the ARDUINO platform
Lightweight Face Image Quality Assessment
LightQNet This is a demo code of training and testing [LightQNet] using Tensorflow. Uncertainty Losses: IDQ loss PCNet loss Uncertainty Networks: Mobi
How to Train a GAN? Tips and tricks to make GANs work
(this list is no longer maintained, and I am not sure how relevant it is in 2020) How to Train a GAN? Tips and tricks to make GANs work While research
Train CPPNs as a Generative Model, using Generative Adversarial Networks and Variational Autoencoder techniques to produce high resolution images.
cppn-gan-vae tensorflow Train Compositional Pattern Producing Network as a Generative Model, using Generative Adversarial Networks and Variational Aut
STBP is a way to train SNN with datasets by Backward propagation.
Spiking neural network (SNN), compared with depth neural network (DNN), has faster processing speed, lower energy consumption and more biological interpretability, which is expected to approach Strong AI.
🚪✊Knock Knock: Get notified when your training ends with only two additional lines of code
Knock Knock A small library to get a notification when your training is complete or when it crashes during the process with two additional lines of co
EZ graph is an easy to use AI solution that allows you to make and train your neural networks without a single line of code.
EZ-Graph EZ Graph is a GUI that allows users to make and train neural networks without writing a single line of code. Requirements python 3 pandas num
Train DeepLab for Semantic Image Segmentation
Train DeepLab for Semantic Image Segmentation Martin Kersner, [email protected] This repository contains scripts for training DeepLab for Semantic I
A Pytorch implementation of MoveNet from Google. Include training code and pre-train model.
Movenet.Pytorch Intro MoveNet is an ultra fast and accurate model that detects 17 keypoints of a body. This is A Pytorch implementation of MoveNet fro
Use MATLAB to simulate the signal and extract features. Use PyTorch to build and train deep network to do spectrum sensing.
Deep-Learning-based-Spectrum-Sensing Use MATLAB to simulate the signal and extract features. Use PyTorch to build and train deep network to do spectru
An implementation of the Contrast Predictive Coding (CPC) method to train audio features in an unsupervised fashion.
CPC_audio This code implements the Contrast Predictive Coding algorithm on audio data, as described in the paper Unsupervised Pretraining Transfers we
A simple app that helps to train quick calculations.
qtcounter A simple app that helps to train quick calculations. Usage Manual Clone the repo in a folder using git clone https://github.com/Froloket64/q
Unofficial reimplementation of ECAPA-TDNN for speaker recognition (EER=0.86 for Vox1_O when train only in Vox2)
Introduction This repository contains my unofficial reimplementation of the standard ECAPA-TDNN, which is the speaker recognition in VoxCeleb2 dataset
An example showing how to use jax to train resnet50 on multi-node multi-GPU
jax-multi-gpu-resnet50-example This repo shows how to use jax for multi-node multi-GPU training. The example is adapted from the resnet50 example in d
Trains an OpenNMT PyTorch model and SentencePiece tokenizer.
Trains an OpenNMT PyTorch model and SentencePiece tokenizer. Designed for use with Argos Translate and LibreTranslate.
Train a state-of-the-art yolov3 object detector from scratch!
TrainYourOwnYOLO: Building a Custom Object Detector from Scratch This repo let's you train a custom image detector using the state-of-the-art YOLOv3 c
The Self-Supervised Learner can be used to train a classifier with fewer labeled examples needed using self-supervised learning.
Published by SpaceML • About SpaceML • Quick Colab Example Self-Supervised Learner The Self-Supervised Learner can be used to train a classifier with
A framework to train language models to learn invariant representations.
Invariant Language Modeling Implementation of the training for invariant language models. Motivation Modern pretrained language models are critical co
Gradient-free global optimization algorithm for multidimensional functions based on the low rank tensor train format
ttopt Description Gradient-free global optimization algorithm for multidimensional functions based on the low rank tensor train (TT) format and maximu
Tangram makes it easy for programmers to train, deploy, and monitor machine learning models.
Tangram Website | Discord Tangram makes it easy for programmers to train, deploy, and monitor machine learning models. Run tangram train to train a mo
Making self-supervised learning work on molecules by using their 3D geometry to pre-train GNNs. Implemented in DGL and Pytorch Geometric.
3D Infomax improves GNNs for Molecular Property Prediction Video | Paper We pre-train GNNs to understand the geometry of molecules given only their 2D
This repository contains the files for running the Patchify GUI.
Repository Name Train-Test-Validation-Dataset-Generation App Name Patchify Description This app is designed for crop images and creating smal
Framework to build and train RL algorithms
RayLink RayLink is a RL framework used to build and train RL algorithms. RayLink was used to build a RL framework, and tested in a large-scale multi-a
TLDR; Train custom adaptive filter optimizers without hand tuning or extra labels.
AutoDSP TLDR; Train custom adaptive filter optimizers without hand tuning or extra labels. About Adaptive filtering algorithms are commonplace in sign
HeatNet is a python package that provides tools to build, train and evaluate neural networks designed to predict extreme heat wave events globally on daily to subseasonal timescales.
HeatNet HeatNet is a python package that provides tools to build, train and evaluate neural networks designed to predict extreme heat wave events glob
Train 🤗-transformers model with Poutyne.
poutyne-transformers Train 🤗 -transformers models with Poutyne. Installation pip install poutyne-transformers Example import torch from transformers
Reimplement of SimSwap training code
SimSwap-train Reimplement of SimSwap training code Instructions 1.Environment Preparation (1)Refer to the README document of SIMSWAP to configure the
Quickly and easily create / train a custom DeepDream model
Dream-Creator This project aims to simplify the process of creating a custom DeepDream model by using pretrained GoogleNet models and custom image dat
A Tools that help Data Scientists and ML engineers train and deploy ML models.
Domino Research This repo contains projects under active development by the Domino R&D team. We build tools that help Data Scientists and ML engineers
Train a deep learning net with OpenStreetMap features and satellite imagery.
DeepOSM Classify roads and features in satellite imagery, by training neural networks with OpenStreetMap (OSM) data. DeepOSM can: Download a chunk of
NLPIR tutorial: pretrain for IR. pre-train on raw textual corpus, fine-tune on MS MARCO Document Ranking
pretrain4ir_tutorial NLPIR tutorial: pretrain for IR. pre-train on raw textual corpus, fine-tune on MS MARCO Document Ranking 用作NLPIR实验室, Pre-training
This repository contains a set of codes to run (i.e., train, perform inference with, evaluate) a diarization method called EEND-vector-clustering.
EEND-vector clustering The EEND-vector clustering (End-to-End-Neural-Diarization-vector clustering) is a speaker diarization framework that integrates
load .txt to train YOLOX, same as Yolo others
YOLOX train your data you need generate data.txt like follow format (per line- one image). prepare one data.txt like this: img_path1 x1,y1,x2,y2,clas
Train GPT-3 model on V100(16GB Mem) Using improved Transformer.
GPT-X using transformer pytorch
Codes to pre-train Japanese T5 models
t5-japanese Codes to pre-train a T5 (Text-to-Text Transfer Transformer) model pre-trained on Japanese web texts. The model is available at https://hug
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
Music Source Separation; Train & Eval & Inference piplines and pretrained models we used for 2021 ISMIR MDX Challenge.
Music Source Separation with Channel-wise Subband Phase Aware ResUnet (CWS-PResUNet) Introduction This repo contains the pretrained Music Source Separ
IMS-Toucan is a toolkit to train state-of-the-art Speech Synthesis models
IMS-Toucan is a toolkit to train state-of-the-art Speech Synthesis models. Everything is pure Python and PyTorch based to keep it as simple and beginner-friendly, yet powerful as possible.
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