1438 Repositories
Python model-monitoring Libraries
Use Django admin to manage drip campaign emails using querysets on Django's User model.
Django Drip Drip campaigns are pre-written sets of emails sent to customers or prospects over time. Django Drips lets you use the admin to manage drip
Sentry is cross-platform application monitoring, with a focus on error reporting.
Users and logs provide clues. Sentry provides answers. What's Sentry? Sentry is a service that helps you monitor and fix crashes in realtime. The serv
[ICCV 2021] Official Tensorflow Implementation for "Single Image Defocus Deblurring Using Kernel-Sharing Parallel Atrous Convolutions"
KPAC: Kernel-Sharing Parallel Atrous Convolutional block This repository contains the official Tensorflow implementation of the following paper: Singl
IndoBERTweet is the first large-scale pretrained model for Indonesian Twitter. Published at EMNLP 2021 (main conference)
IndoBERTweet 🐦 🇮🇩 1. Paper Fajri Koto, Jey Han Lau, and Timothy Baldwin. IndoBERTweet: A Pretrained Language Model for Indonesian Twitter with Effe
[EMNLP 2021] LM-Critic: Language Models for Unsupervised Grammatical Error Correction
LM-Critic: Language Models for Unsupervised Grammatical Error Correction This repo provides the source code & data of our paper: LM-Critic: Language M
Code & Models for 3DETR - an End-to-end transformer model for 3D object detection
3DETR: An End-to-End Transformer Model for 3D Object Detection PyTorch implementation and models for 3DETR. 3DETR (3D DEtection TRansformer) is a simp
Code for the paper in Findings of EMNLP 2021: "EfficientBERT: Progressively Searching Multilayer Perceptron via Warm-up Knowledge Distillation".
This repository contains the code for the paper in Findings of EMNLP 2021: "EfficientBERT: Progressively Searching Multilayer Perceptron via Warm-up Knowledge Distillation".
The training code for the 4th place model at MDX 2021 leaderboard A.
The training code for the 4th place model at MDX 2021 leaderboard A.
Must-read papers on improving efficiency for pre-trained language models.
Must-read papers on improving efficiency for pre-trained language models.
DAFNe: A One-Stage Anchor-Free Deep Model for Oriented Object Detection
DAFNe: A One-Stage Anchor-Free Deep Model for Oriented Object Detection Code for our Paper DAFNe: A One-Stage Anchor-Free Deep Model for Oriented Obje
Channel Pruning for Accelerating Very Deep Neural Networks (ICCV'17)
Channel Pruning for Accelerating Very Deep Neural Networks (ICCV'17)
[EMNLP 2021] Distantly-Supervised Named Entity Recognition with Noise-Robust Learning and Language Model Augmented Self-Training
RoSTER The source code used for Distantly-Supervised Named Entity Recognition with Noise-Robust Learning and Language Model Augmented Self-Training, p
Feed forward VQGAN-CLIP model, where the goal is to eliminate the need for optimizing the latent space of VQGAN for each input prompt
Feed forward VQGAN-CLIP model, where the goal is to eliminate the need for optimizing the latent space of VQGAN for each input prompt. This is done by
A custom DeepStack model for detecting 16 human actions.
DeepStack_ActionNET This repository provides a custom DeepStack model that has been trained and can be used for creating a new object detection API fo
Demonstrates how to divide a DL model into multiple IR model files (division) and introduce a simplest way to implement a custom layer works with OpenVINO IR models.
Demonstration of OpenVINO techniques - Model-division and a simplest-way to support custom layers Description: Model Optimizer in Intel(r) OpenVINO(tm
G-NIA model from "Single Node Injection Attack against Graph Neural Networks" (CIKM 2021)
Single Node Injection Attack against Graph Neural Networks This repository is our Pytorch implementation of our paper: Single Node Injection Attack ag
Demonstrates iterative FGSM on Apple's NeuralHash model.
apple-neuralhash-attack Demonstrates iterative FGSM on Apple's NeuralHash model. TL;DR: It is possible to apply noise to CSAM images and make them loo
UniLM AI - Large-scale Self-supervised Pre-training across Tasks, Languages, and Modalities
Pre-trained (foundation) models across tasks (understanding, generation and translation), languages (100+ languages), and modalities (language, image, audio, vision + language, audio + language, etc.)
Python scripts form performing stereo depth estimation using the HITNET model in ONNX.
ONNX-HITNET-Stereo-Depth-estimation Python scripts form performing stereo depth estimation using the HITNET model in ONNX. Stereo depth estimation on
Python scripts form performing stereo depth estimation using the HITNET model in Tensorflow Lite.
TFLite-HITNET-Stereo-depth-estimation Python scripts form performing stereo depth estimation using the HITNET model in Tensorflow Lite. Stereo depth e
This repository contains the official release of the model "BanglaBERT" and associated downstream finetuning code and datasets introduced in the paper titled "BanglaBERT: Combating Embedding Barrier in Multilingual Models for Low-Resource Language Understanding".
BanglaBERT This repository contains the official release of the model "BanglaBERT" and associated downstream finetuning code and datasets introduced i
A web app for presenting my research in BEM(building energy model) simulation
BEM(building energy model)-SIM-APP The is a web app presenting my research in BEM(building energy model) calibration. You can play around with some pa
Tutorial to pretrain & fine-tune a 🤗 Flax T5 model on a TPUv3-8 with GCP
Pretrain and Fine-tune a T5 model with Flax on GCP This tutorial details how pretrain and fine-tune a FlaxT5 model from HuggingFace using a TPU VM ava
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
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)
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
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
Prototype for Baby Action Detection and Classification
Baby Action Detection Table of Contents About Install Run Predictions Demo About An attempt to harness the power of Deep Learning to come up with a so
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
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.
This is a telegram bot hosted by a Raspberry Pi equipped with a temperature and humidity sensor. The bot is capable of sending plots and readings.
raspy-temperature-bot This is a telegram bot hosted by a Raspberry Pi equipped with a temperature and humidity sensor. The bot is capable of sending p
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
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
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
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
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
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
CURSO PROMETHEUS E GRAFANA: Observability in a real world
Curso de monitoração com o Prometheus Esse curso ensina como usar o Prometheus como uma ferramenta integrada de monitoração, entender seus conceitos,
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
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
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
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
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
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
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.
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,
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.
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
Slack bot for monitoring your Metaflow flows!
Metaflowbot - Slack Bot for your Metaflow flows! Metaflowbot makes it fun and easy to monitor your Metaflow runs, past and present. Imagine starting a
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
esguard provides a Python decorator that waits for processing while monitoring the load of Elasticsearch.
esguard esguard provides a Python decorator that waits for processing while monitoring the load of Elasticsearch. Quick Start You need to launch elast
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
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
A simple object model for the Notion SDK.
A simplified object model for the Notion SDK. This is loosely modeled after concepts found in SQLAlchemy.
API for the GPT-J language model 🦜. Including a FastAPI backend and a streamlit frontend
gpt-j-api 🦜 An API to interact with the GPT-J language model. You can use and test the model in two different ways: Streamlit web app at http://api.v
A state of the art of new lightweight YOLO model implemented by TensorFlow 2.
CSL-YOLO: A New Lightweight Object Detection System for Edge Computing This project provides a SOTA level lightweight YOLO called "Cross-Stage Lightwe
A Multi-modal Model Chinese Spell Checker Released on ACL2021.
ReaLiSe ReaLiSe is a multi-modal Chinese spell checking model. This the office code for the paper Read, Listen, and See: Leveraging Multimodal Informa
Repository for reproducing `Model-Based Robust Deep Learning`
Model-Based Robust Deep Learning (MBRDL) In this repository, we include the code necessary for reproducing the code used in Model-Based Robust Deep Le
Code for Motion Representations for Articulated Animation paper
Motion Representations for Articulated Animation This repository contains the source code for the CVPR'2021 paper Motion Representations for Articulat
Versatile Generative Language Model
Versatile Generative Language Model This is the implementation of the paper: Exploring Versatile Generative Language Model Via Parameter-Efficient Tra
Active and Sample-Efficient Model Evaluation
Active Testing: Sample-Efficient Model Evaluation Hi, good to see you here! 👋 This is code for "Active Testing: Sample-Efficient Model Evaluation". P
PyTorch implementation of MuseMorphose, a Transformer-based model for music style transfer.
MuseMorphose This repository contains the official implementation of the following paper: Shih-Lun Wu, Yi-Hsuan Yang MuseMorphose: Full-Song and Fine-
A modified version of DeepMind's Alphafold2 to divide CPU part (MSA and template searching) and GPU part (prediction model)
ParallelFold Author: Bozitao Zhong This is a modified version of DeepMind's Alphafold2 to divide CPU part (MSA and template searching) and GPU part (p
Pairwise model for commonlit competition
Pairwise model for commonlit competition To run: - install requirements - create input directory with train_folds.csv and other competition data - cd
Evidently helps analyze machine learning models during validation or production monitoring
Evidently helps analyze machine learning models during validation or production monitoring. The tool generates interactive visual reports and JSON profiles from pandas DataFrame or csv files. Currently 6 reports are available.
Pytorch implementation of the paper "Optimization as a Model for Few-Shot Learning"
Optimization as a Model for Few-Shot Learning This repo provides a Pytorch implementation for the Optimization as a Model for Few-Shot Learning paper.
A Structured Self-attentive Sentence Embedding
Structured Self-attentive sentence embeddings Implementation for the paper A Structured Self-Attentive Sentence Embedding, which was published in ICLR
🐥A PyTorch implementation of OpenAI's finetuned transformer language model with a script to import the weights pre-trained by OpenAI
PyTorch implementation of OpenAI's Finetuned Transformer Language Model This is a PyTorch implementation of the TensorFlow code provided with OpenAI's