1410 Repositories
Python auto-regressive-models Libraries
Convert onnx models to pytorch.
onnx2torch onnx2torch is an ONNX to PyTorch converter. Our converter: Is easy to use – Convert the ONNX model with the function call convert; Is easy
Robbing the FED: Directly Obtaining Private Data in Federated Learning with Modified Models
Robbing the FED: Directly Obtaining Private Data in Federated Learning with Modified Models This repo contains a barebones implementation for the atta
The python SDK for Eto, the AI focused data platform for teams bringing AI models to production
Eto Labs Python SDK This is the python SDK for Eto, the AI focused data platform for teams bringing AI models to production. The python SDK makes it e
Code for Temporally Abstract Partial Models
Code for Temporally Abstract Partial Models Accompanies the code for the experimental section of the paper: Temporally Abstract Partial Models, Khetar
Code for WECHSEL: Effective initialization of subword embeddings for cross-lingual transfer of monolingual language models.
WECHSEL Code for WECHSEL: Effective initialization of subword embeddings for cross-lingual transfer of monolingual language models. arXiv: https://arx
Experiments on continual learning from a stream of pretrained models.
Ex-model CL Ex-model continual learning is a setting where a stream of experts (i.e. model's parameters) is available and a CL model learns from them
Discovering Explanatory Sentences in Legal Case Decisions Using Pre-trained Language Models.
Statutory Interpretation Data Set This repository contains the data set created for the following research papers: Savelka, Jaromir, and Kevin D. Ashl
Type annotations builder for boto3 compatible with VSCode, PyCharm, Emacs, Sublime Text, pyright and mypy.
mypy_boto3_builder Type annotations builder for boto3-stubs project. Compatible with VSCode, PyCharm, Emacs, Sublime Text, mypy, pyright and other too
AdamW optimizer for bfloat16 models in pytorch.
Image source AdamW optimizer for bfloat16 models in pytorch. Bfloat16 is currently an optimal tradeoff between range and relative error for deep netwo
Code for WECHSEL: Effective initialization of subword embeddings for cross-lingual transfer of monolingual language models.
WECHSEL Code for WECHSEL: Effective initialization of subword embeddings for cross-lingual transfer of monolingual language models. arXiv: https://arx
MLReef is an open source ML-Ops platform that helps you collaborate, reproduce and share your Machine Learning work with thousands of other users.
The collaboration platform for Machine Learning MLReef is an open source ML-Ops platform that helps you collaborate, reproduce and share your Machine
This repos is auto action which generating a wordcloud made by Twitter.
auto_tweet_wordcloud This repos is auto action which generating a wordcloud made by Twitter. Preconditions Install Python dependencies pip install -r
Integrate GraphQL with your Pydantic models
graphene-pydantic A Pydantic integration for Graphene. Installation pip install "graphene-pydantic" Examples Here is a simple Pydantic model: import u
Certbot is EFF's tool to obtain certs from Let's Encrypt and (optionally) auto-enable HTTPS on your server.
Certbot is EFF's tool to obtain certs from Let's Encrypt and (optionally) auto-enable HTTPS on your server. It can also act as a client for any other CA that uses the ACME protocol.
Using image super resolution models with vapoursynth and speeding them up with TensorRT
vs-RealEsrganAnime-tensorrt-docker Using image super resolution models with vapoursynth and speeding them up with TensorRT. Also a docker image since
Code for paper: "Spinning Language Models for Propaganda-As-A-Service"
Spinning Language Models for Propaganda-As-A-Service This is the source code for the Arxiv version of the paper. You can use this Google Colab to expl
A FAIR dataset of TCV experimental results for validating edge/divertor turbulence models.
TCV-X21 validation for divertor turbulence simulations Quick links Intro Welcome to TCV-X21. We're glad you've found us! This repository is designed t
Pydantic models for pywttr and aiopywttr.
Pydantic models for pywttr and aiopywttr.
A minimal, standalone viewer for 3D animations stored as stop-motion sequences of individual .obj mesh files.
ObjSequenceViewer V0.5 A minimal, standalone viewer for 3D animations stored as stop-motion sequences of individual .obj mesh files. Installation: pip
PyTorch implementation of normalizing flow models
PyTorch implementation of normalizing flow models
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
PyAbsorp is a python module that has the main focus to help estimate the Sound Absorption Coefficient.
This is a package developed to be use to find the Sound Absorption Coefficient through some implemented models, like Biot-Allard, Johnson-Champoux and
A JSON-friendly data structure which allows both object attributes and dictionary keys and values to be used simultaneously and interchangeably.
A JSON-friendly data structure which allows both object attributes and dictionary keys and values to be used simultaneously and interchangeably.
SeqAttack: a framework for adversarial attacks on token classification models
A framework for adversarial attacks against token classification models
Auto grind btdb2 exp for tower
Bloons TD Battles 2 EXP Grinder Auto grind btdb2 exp for towers Setup I suggest checking out every screenshot to see what they are supposed to be, so
Users can free try their models on SIDD dataset based on this code
SIDD benchmark 1 Train python train.py If you want to train your network, just modify the yaml in the options folder. 2 Validation python validation.p
PyTorch implementation of a collections of scalable Video Transformer Benchmarks.
PyTorch implementation of Video Transformer Benchmarks This repository is mainly built upon Pytorch and Pytorch-Lightning. We wish to maintain a colle
easyNeuron is a simple way to create powerful machine learning models, analyze data and research cutting-edge AI.
easyNeuron is a simple way to create powerful machine learning models, analyze data and research cutting-edge AI.
A lightweight library designed to accelerate the process of training PyTorch models by providing a minimal
A lightweight library designed to accelerate the process of training PyTorch models by providing a minimal, but extensible training loop which is flexible enough to handle the majority of use cases, and capable of utilizing different hardware options with no code changes required.
Official code for "Maximum Likelihood Training of Score-Based Diffusion Models", NeurIPS 2021 (spotlight)
Maximum Likelihood Training of Score-Based Diffusion Models This repo contains the official implementation for the paper Maximum Likelihood Training o
Some 3Commas helper bots, AltRank, GalaxyScore, Watchlist, Auto-Compound
3Commas Cyber Bot Helpers A collection of 3Commas bot helpers I wrote. (collection will grow over time) Disclaimer THE SOFTWARE IS PROVIDED "AS IS", W
Autoregressive Models in PyTorch.
Autoregressive This repository contains all the necessary PyTorch code, tailored to my presentation, to train and generate data from WaveNet-like auto
Models, datasets and tools for Facial keypoints detection
Template for Data Science Project This repo aims to give a robust starting point to any Data Science related project. It contains readymade tools setu
Auto Liker, Auto Reaction, Auto Comment, Auto Follower Tool. RajeLiker Credit Hacker.
Auto Liker, Auto Reaction, Auto Comment, Auto Follower Tool. RajeLiker Credit Hacker. Unlimited RajeLiker Credit Hack. Thanks To RajeLiker.
Explainability of the Implications of Supervised and Unsupervised Face Image Quality Estimations Through Activation Map Variation Analyses in Face Recognition Models
Explainable_FIQA_WITH_AMVA Note This is the official repository of the paper: Explainability of the Implications of Supervised and Unsupervised Face I
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.
Visual Adversarial Imitation Learning using Variational Models (VMAIL)
Visual Adversarial Imitation Learning using Variational Models (VMAIL) This is the official implementation of the NeurIPS 2021 paper. Project website
A collection of models, views, middlewares, and forms to help secure a Django project.
Django-Security This package offers a number of models, views, middlewares and forms to facilitate security hardening of Django applications. Full doc
RuleBERT: Teaching Soft Rules to Pre-Trained Language Models
RuleBERT: Teaching Soft Rules to Pre-Trained Language Models (Paper) (Slides) (Video) RuleBERT is a pre-trained language model that has been fine-tune
An MLOps framework to package, deploy, monitor and manage thousands of production machine learning models
Seldon Core: Blazing Fast, Industry-Ready ML An open source platform to deploy your machine learning models on Kubernetes at massive scale. Overview S
Uni-Fold: Training your own deep protein-folding models.
Uni-Fold: Training your own deep protein-folding models. This package provides and implementation of a trainable, Transformer-based deep protein foldi
Torchrecipes provides a set of reproduci-able, re-usable, ready-to-run RECIPES for training different types of models, across multiple domains, on PyTorch Lightning.
Recipes are a standard, well supported set of blueprints for machine learning engineers to rapidly train models using the latest research techniques without significant engineering overhead.Specifically, recipes aims to provide- Consistent access to pre-trained SOTA models ready for production- Reference implementations for SOTA research reproducibility, and infrastructure to guarantee correctness, efficiency, and interoperability.
State-of-the-art NLP through transformer models in a modular design and consistent APIs.
Trapper (Transformers wRAPPER) Trapper is an NLP library that aims to make it easier to train transformer based models on downstream tasks. It wraps h
EMNLP 2021 paper Models and Datasets for Cross-Lingual Summarisation.
This repository contains data and code for our EMNLP 2021 paper Models and Datasets for Cross-Lingual Summarisation. Please contact me at [email protected]
A modular application for performing anomaly detection in networks
Deep-Learning-Models-for-Network-Annomaly-Detection The modular app consists for mainly three annomaly detection algorithms. The system supports model
Model Validation Toolkit is a collection of tools to assist with validating machine learning models prior to deploying them to production and monitoring them after deployment to production.
Model Validation Toolkit is a collection of tools to assist with validating machine learning models prior to deploying them to production and monitoring them after deployment to production.
Rapid experimentation and scaling of deep learning models on molecular and crystal graphs.
LitMatter A template for rapid experimentation and scaling deep learning models on molecular and crystal graphs. How to use Clone this repository and
Markov Attention Models
Introduction This repo contains code for reproducing the results in the paper Graphical Models with Attention for Context-Specific Independence and an
SHRIMP: Sparser Random Feature Models via Iterative Magnitude Pruning
SHRIMP: Sparser Random Feature Models via Iterative Magnitude Pruning This repository is the official implementation of "SHRIMP: Sparser Random Featur
S-attack library. Official implementation of two papers "Are socially-aware trajectory prediction models really socially-aware?" and "Vehicle trajectory prediction works, but not everywhere".
S-attack library: A library for evaluating trajectory prediction models This library contains two research projects to assess the trajectory predictio
local pypi server (custom packages and auto-mirroring of pypi)
localshop A PyPI server which automatically proxies and mirrors PyPI packages based upon packages requested. It has support for multiple indexes and t
Machine translation models released by the Gourmet project
Gourmet Models Overview The Gourmet project has released several machine translation models to translate low-resource languages. This repository conta
Uni-Fold: Training your own deep protein-folding models
Uni-Fold: Training your own deep protein-folding models. This package provides an implementation of a trainable, Transformer-based deep protein foldin
The easiest tool for extracting radiomics features and training ML models on them.
Simple pipeline for experimenting with radiomics features Installation git clone https://github.com/piotrekwoznicki/ClassyRadiomics.git cd classrad pi
✨️🐍 SPARQL endpoint built with RDFLib to serve machine learning models, or any other logic implemented in Python
✨ SPARQL endpoint for RDFLib rdflib-endpoint is a SPARQL endpoint based on a RDFLib Graph to easily serve machine learning models, or any other logic
Data pipelines for both TensorFlow and PyTorch!
rapidnlp-datasets Data pipelines for both TensorFlow and PyTorch ! If you want to load public datasets, try: tensorflow/datasets huggingface/datasets
Tensorflow implementation of Character-Aware Neural Language Models.
Character-Aware Neural Language Models Tensorflow implementation of Character-Aware Neural Language Models. The original code of author can be found h
A TensorFlow implementation of the Mnemonic Descent Method.
MDM A Tensorflow implementation of the Mnemonic Descent Method. Mnemonic Descent Method: A recurrent process applied for end-to-end face alignment G.
Sarus implementation of classical ML models. The models are implemented using the Keras API of tensorflow 2. Vizualization are implemented and can be seen in tensorboard.
Sarus published models Sarus implementation of classical ML models. The models are implemented using the Keras API of tensorflow 2. Vizualization are
Caffe models in TensorFlow
Caffe to TensorFlow Convert Caffe models to TensorFlow. Usage Run convert.py to convert an existing Caffe model to TensorFlow. Make sure you're using
Run Keras models in the browser, with GPU support using WebGL
**This project is no longer active. Please check out TensorFlow.js.** The Keras.js demos still work but is no longer updated. Run Keras models in the
Tensorflow/Keras Plug-N-Play Deep Learning Models Compilation
DeepBay This project was created with the objective of compile Machine Learning Architectures created using Tensorflow or Keras. The architectures mus
A design of MIDI language for music generation task, specifically for Natural Language Processing (NLP) models.
MIDI Language Introduction Reference Paper: Pop Music Transformer: Beat-based Modeling and Generation of Expressive Pop Piano Compositions: code This
SLAMP: Stochastic Latent Appearance and Motion Prediction
SLAMP: Stochastic Latent Appearance and Motion Prediction Official implementation of the paper SLAMP: Stochastic Latent Appearance and Motion Predicti
Face Detection with DLIB
Face Detection with DLIB In this project, we have detected our face with dlib and opencv libraries. Setup This Project Install DLIB & OpenCV You can i
The Codebase for Causal Distillation for Language Models.
Causal Distillation for Language Models Zhengxuan Wu*,Atticus Geiger*, Josh Rozner, Elisa Kreiss, Hanson Lu, Thomas Icard, Christopher Potts, Noah D.
Official implementation of the paper Label-Efficient Semantic Segmentation with Diffusion Models
Label-Efficient Semantic Segmentation with Diffusion Models Official implementation of the paper Label-Efficient Semantic Segmentation with Diffusion
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
Self-adjusting, auto-compounding multi-pair DCA crypto trading bot using Python, AWS Lambda & 3Commas API
Self-adjusting, auto-compounding multi-pair DCA crypto trading bot using Python, AWS Lambda & 3Commas API The following code describes how we can leve
An OpenAI-Gym Package for Training and Testing Reinforcement Learning algorithms with OpenSim Models
Authors: Utkarsh A. Mishra and Dr. Dimitar Stanev Advisors: Dr. Dimitar Stanev and Prof. Auke Ijspeert, Biorobotics Laboratory (BioRob), EPFL Video Pl
Convert ONNX model graph to Keras model format.
Convert ONNX model graph to Keras model format.
FedTorch is an open-source Python package for distributed and federated training of machine learning models using PyTorch distributed API
FedTorch is a generic repository for benchmarking different federated and distributed learning algorithms using PyTorch Distributed API.
You will need to install a few python packages for this one.
Features Bait support Auto repair will repair every 10 catches Anti detection (still a work in progress) but using random times and click positions Pr
A comprehensive set of fairness metrics for datasets and machine learning models, explanations for these metrics, and algorithms to mitigate bias in datasets and models.
AI Fairness 360 (AIF360) The AI Fairness 360 toolkit is an extensible open-source library containg techniques developed by the research community to h
MetaAvatar: Learning Animatable Clothed Human Models from Few Depth Images
MetaAvatar: Learning Animatable Clothed Human Models from Few Depth Images This repository contains the implementation of our paper MetaAvatar: Learni
A auto clock-in script based on python3 for BJUTer.
Introduction A auto clock-in script based on python3 for BJUTer. It could clock in at 9:00 a.m everyday. The script is inspired by tsosunchia What can
Official Pytorch implementation for 2021 ICCV paper "Learning Motion Priors for 4D Human Body Capture in 3D Scenes" and trained models / data
Learning Motion Priors for 4D Human Body Capture in 3D Scenes (LEMO) Official Pytorch implementation for 2021 ICCV (oral) paper "Learning Motion Prior
A Chinese to English Neural Model Translation Project
ZH-EN NMT Chinese to English Neural Machine Translation This project is inspired by Stanford's CS224N NMT Project Dataset used in this project: News C
Code for the Paper "Diffusion Models for Handwriting Generation"
Code for the Paper "Diffusion Models for Handwriting Generation"
Implementation of Google Brain's WaveGrad high-fidelity vocoder
WaveGrad Implementation (PyTorch) of Google Brain's high-fidelity WaveGrad vocoder (paper). First implementation on GitHub with high-quality generatio
DiffWave is a fast, high-quality neural vocoder and waveform synthesizer.
DiffWave DiffWave is a fast, high-quality neural vocoder and waveform synthesizer. It starts with Gaussian noise and converts it into speech via itera
Symbolic Music Generation with Diffusion Models
Symbolic Music Generation with Diffusion Models Supplementary code release for our work Symbolic Music Generation with Diffusion Models. Installation
Implementation of "Adversarial purification with Score-based generative models", ICML 2021
Adversarial Purification with Score-based Generative Models by Jongmin Yoon, Sung Ju Hwang, Juho Lee This repository includes the official PyTorch imp
Reference implementation for Deep Unsupervised Learning using Nonequilibrium Thermodynamics
Diffusion Probabilistic Models This repository provides a reference implementation of the method described in the paper: Deep Unsupervised Learning us
Noise Conditional Score Networks (NeurIPS 2019, Oral)
Generative Modeling by Estimating Gradients of the Data Distribution This repo contains the official implementation for the NeurIPS 2019 paper Generat
The official PyTorch implementation for NCSNv2 (NeurIPS 2020)
Improved Techniques for Training Score-Based Generative Models This repo contains the official implementation for the paper Improved Techniques for Tr
PyTorch reimplementation of Diffusion Models
PyTorch pretrained Diffusion Models A PyTorch reimplementation of Denoising Diffusion Probabilistic Models with checkpoints converted from the author'
Denoising Diffusion Probabilistic Models
Denoising Diffusion Probabilistic Models Jonathan Ho, Ajay Jain, Pieter Abbeel Paper: https://arxiv.org/abs/2006.11239 Website: https://hojonathanho.g
Denoising Diffusion Implicit Models
Denoising Diffusion Implicit Models (DDIM) Jiaming Song, Chenlin Meng and Stefano Ermon, Stanford Implements sampling from an implicit model that is t
Diffusion Probabilistic Models for 3D Point Cloud Generation (CVPR 2021)
Diffusion Probabilistic Models for 3D Point Cloud Generation [Paper] [Code] The official code repository for our CVPR 2021 paper "Diffusion Probabilis
Jax/Flax implementation of Variational-DiffWave.
jax-variational-diffwave Jax/Flax implementation of Variational-DiffWave. (Zhifeng Kong et al., 2020, Diederik P. Kingma et al., 2021.) DiffWave with
PyTorch toolkit for biomedical imaging
farabio is a minimal PyTorch toolkit for out-of-the-box deep learning support in biomedical imaging. For further information, see Wikis and Docs.
A collection of resources and papers on Diffusion Models, a darkhorse in the field of Generative Models
This repository contains a collection of resources and papers on Diffusion Models and Score-based Models. If there are any missing valuable resources
Quick program made to generate alpha and delta tables for Hidden Markov Models
HMM_Calc Functions for generating Alpha and Delta tables from a Hidden Markov Model. Parameters: a: Matrix of transition probabilities. a[i][j] = a_{i
Very Sempil Bot Auto Filter bot
SAMANTHA_BOT Very Sempil Bot Auto Filter bot ##[ # 𝐂𝐋𝐈𝐂𝐊 𝐁𝐄𝐋𝐎𝐖 𝐈𝐌𝐀𝐆𝐄 𝐓𝐎 𝐃𝐄𝐏𝐋𝐎𝐘 👇 👇 👇 Auto Filter Manuel Filter IMDB Admin Co
Tensorflow implementation of Semi-supervised Sequence Learning (https://arxiv.org/abs/1511.01432)
Transfer Learning for Text Classification with Tensorflow Tensorflow implementation of Semi-supervised Sequence Learning(https://arxiv.org/abs/1511.01
Pipeline for training LSA models using Scikit-Learn.
Latent Semantic Analysis Pipeline for training LSA models using Scikit-Learn. Usage Instead of writing custom code for latent semantic analysis, you j
FIVE, Vulnerability Scanner And Mass Exploiter, made for pentesting.
$ FIVE - FIVE is a Pentesting Framework to Test the Security & Integrity of a Website, or Multiple Websites. $ Info FIVE Was Made After Vulnnr to Prod
GPT-3: Language Models are Few-Shot Learners
GPT-3: Language Models are Few-Shot Learners arXiv link Recent work has demonstrated substantial gains on many NLP tasks and benchmarks by pre-trainin
Official implementations for various pre-training models of ERNIE-family, covering topics of Language Understanding & Generation, Multimodal Understanding & Generation, and beyond.
English|简体中文 ERNIE是百度开创性提出的基于知识增强的持续学习语义理解框架,该框架将大数据预训练与多源丰富知识相结合,通过持续学习技术,不断吸收海量文本数据中词汇、结构、语义等方面的知识,实现模型效果不断进化。ERNIE在累积 40 余个典型 NLP 任务取得 SOTA 效果,并在 G