Python Model-analysis Resources

Reverse_Engineering_GMs Official Pytorch implementation of paper "Reverse Engineering of Generative Models: Inferring Model Hyperparameters from Gener

LoRA: Low-Rank Adaptation of Large Language Models This repo contains the implementation of LoRA in GPT-2 and steps to replicate the results in our re

SolvationAnalysis The macroscopic behavior of a liquid is determined by its microscopic structure. For ionic systems, like batteries and many enzymes,

Swin Transformer (Tensorflow) Tensorflow reimplementation of Swin Transformer model. Based on Official Pytorch implementation. Requirements tensorflow

Denoising Diffusion Probabilistic Model for Proteins Implementation of Denoising Diffusion Probabilistic Model in Pytorch. It is a new approach to gen

modelvshuman is a Python library to benchmark the gap between human and machine vision. Using this library, both PyTorch and TensorFlow models can be evaluated on 17 out-of-distribution datasets with high-quality human comparison data.

Orientation independent Möbius CNNs This repository implements and evaluates convolutional networks on the Möbius strip as toy model instantiations of

deep_autoviml Build keras pipelines and models in a single line of code! Table of Contents Motivation How it works Technology Install Usage API Image

On the model-based stochastic value gradient for continuous reinforcement learning This repository is by Brandon Amos, Samuel Stanton, Denis Yarats, a

Optimal Model Design for Reinforcement Learning This repository contains JAX code for the paper Control-Oriented Model-Based Reinforcement Learning wi

MOT Tracked object bounding box association (CenterTrack++) New association method based on CenterTrack. Two new branches (Tracked Size and IOU) are a

Sparsity Probe: Analysis tool for Deep Learning Models This repository is a limited implementation of Sparsity Probe: Analysis tool for Deep Learning

Automatic Weapon Detection Deployment of a hybrid model for automatic weapon detection/ anomaly detection for surveillance applications. Loved the pro

InsightFace: 2D and 3D Face Analysis Project on MXNet and PyTorch

Handwritten-Text-Recognition Handwritten Text Recognition (HTR) system implemented with TensorFlow (TF) and trained on the IAM off-line HTR dataset. T

HNECV This repository provides a reference implementation of HNECV as described in the paper: HNECV: Heterogeneous Network Embedding via Cloud model a

BCNet This repository includes the some source code and related dataset of paper BCNet: Learning Body and Cloth Shape from A Single Image, ECCV 2020,

Summary Loop This repository contains the code for ACL2020 paper: The Summary Loop: Learning to Write Abstractive Summaries Without Examples. Training

ProcrustEs-KGE Paddle implementation for Highly Efficient Knowledge Graph Embedding Learning with Orthogonal Procrustes Analysis 🙈 A more detailed re

The lottery ticket hypothesis (LTH) reveals the existence of winning tickets (sparse but critical subnetworks) for dense networks, that can be trained in isolation from random initialization to match the latter’s accuracies.

Sentance Parser Executing the Program Make sure Python 3.6+ is installed. Install requirements $ pip install requirements.txt Run the program:

SYMPAIS: Symbolic Parallel Adaptive Importance Sampling for Probabilistic Program Analysis Overview | Installation | Documentation | Examples | Notebo

DiffSinger - PyTorch Implementation PyTorch implementation of DiffSinger: Diffusion Acoustic Model for Singing Voice Synthesis (TTS Extension). Status

Model-free Vehicle Tracking and State Estimation in Point Cloud Sequences 1. Introduction This project is for paper Model-free Vehicle Tracking and St

Chinese clinical named entity recognition (CNER) using pre-trained BERT model Introduction Code for paper Chinese clinical named entity recognition wi

ProteinLM We pretrain protein language model based on Megatron-LM framework, and then evaluate the pretrained model results on TAPE (Tasks Assessing P

Quickly train T5 models in just 3 lines of code + ONNX support simpleT5 is built on top of PyTorch-lightning ⚡️ and Transformers 🤗 that lets you quic

SparseML is a toolkit that includes APIs, CLIs, scripts and libraries that apply state-of-the-art sparsification algorithms such as pruning and quantization to any neural network. General, recipe-driven approaches built around these algorithms enable the simplification of creating faster and smaller models for the ML performance community at large.

🔬 A curated list of awesome machine learning strategies & tools in financial market.

APKLeaks - Scanning APK file for URIs, endpoints & secrets.

Overlap-based 3D LiDAR Monte Carlo Localization This repo contains the code for our IROS2020 paper: Learning an Overlap-based Observation Model for 3D

Keyword Spotting Transformer This is the unofficial TensorFlow implementation of the Keyword Spotting Transformer model. This model is used to train o

Using TensorFlow Lite with Python is great for embedded devices based on Linux, such as Raspberry Pi.

Solve Volterra and Fredholm integral equations This Python package estimates Volterra and Fredholm integral equations using known techniques. Installa

Stox A Module to predict the "close price" for the next day and give "technical analysis". It uses a Neural Network and the LSTM algorithm to predict

ProteinBERT is a universal protein language model pretrained on ~106M proteins from the UniRef90 dataset. Through its Python API, the pretrained model can be fine-tuned on any protein-related task in a matter of minutes. Based on our experiments with a wide range of benchmarks, ProteinBERT usually achieves state-of-the-art performance. ProteinBERT is built on TenforFlow/Keras.

NU-Wave: A Diffusion Probabilistic Model for Neural Audio Upsampling For Official repo of NU-Wave: A Diffusion Probabilistic Model for Neural Audio Up

pyprobables is a pure-python library for probabilistic data structures. The goal is to provide the developer with a pure-python implementation of common probabilistic data-structures to use in their work.

A Python package for geospatial analysis and interactive mapping with minimal coding in a Jupyter environment

SiamMOT: Siamese Multi-Object Tracking

Image Crop Analysis This is a repo for the code used for reproducing our Image Crop Analysis paper as shared on our blog post. If you plan to use this

MLP GPT - Jax (wip) A GPT, made only of MLPs, in Jax. The specific MLP to be used are gMLPs with the Spatial Gating Units. Working Pytorch implementat

DDAMS This is the pytorch code for our IJCAI 2021 paper Dialogue Discourse-Aware Graph Model and Data Augmentation for Meeting Summarization [Arxiv Pr

Repository contains the code for 2nd place solution of VinBigData Chest X-ray Abnormalities Detection competition. The goal of competition was to auto

Parallel Tacotron2 Pytorch Implementation of Google's Parallel Tacotron 2: A Non-Autoregressive Neural TTS Model with Differentiable Duration Modeling

NeuralTextures This is repository with inference code for paper "StylePeople: A Generative Model of Fullbody Human Avatars" (CVPR21). This code is for

Fork from https://github.com/huggingface/transformers/tree/86d5fb0b360e68de46d40265e7c707fe68c8015b/examples/pytorch/language-modeling at 2021.05.17.

SmartCane-DL-Model Smart Cane using semantic segmentation 참고한 Github repositoy 🔗 https://github.com/JunHyeok96/Road-Segmentation.git 데이터셋 🔗 https://

Paddle-Image-Models English | 简体中文 A PaddlePaddle version image model zoo. Install Package Install by pip： $ pip install ppim Install by wheel package

Ultra_Fast_Lane_Detection_TensorRT An ultra fast tiny model for lane detection, using onnx_parser, TensorRTAPI to accelerate. our model support for in

RoBERTaABSA This repo contains the code for NAACL 2021 paper titled Does syntax matter? A strong baseline for Aspect-based Sentiment Analysis with RoB

Time series Timeseries Deep Learning Pytorch fastai - State-of-the-art Deep Learning with Time Series and Sequences in Pytorch / fastai

FNet: Mixing Tokens with Fourier Transforms Pytorch implementation of Fnet : Mixing Tokens with Fourier Transforms. Citation: @misc{leethorp2021fnet,

SapBERT: Self-alignment pretraining for BERT This repo holds code for the SapBERT model presented in our NAACL 2021 paper: Self-Alignment Pretraining

CellProfiler is a free open-source software designed to enable biologists without training in computer vision or programming to quantitatively measure phenotypes from thousands of images automatically.

DeepStack_ExDark This repository provides a custom DeepStack model that has been trained and can be used for creating a new object detection API for d

Models Playground 🗂️ Upload a Preprocessed Dataset 🌠 Choose whether to perform Classification or Regression 🦹 Enter the Dependent Variable ?

Crypto_analysis Discription: simple streamlit(screener) app to make MMA and OSC analysis for cyrpto-currenices, and gives resaults for which coins are

It was in January of 2021 that OpenAI announced two new models: DALL-E and CLIP, both multi-modality models connecting texts and images in some way. In this article we are going to implement CLIP model from scratch in PyTorch. OpenAI has open-sourced some of the code relating to CLIP model but I found it intimidating and it was far from something short and simple. I also came across a good tutorial inspired by CLIP model on Keras code examples and I translated some parts of it into PyTorch to build this tutorial totally with our beloved PyTorch!

This repo includes the Pytorch-Geometric implementation of a series of Graph Neural Network (GNN) based fake news detection models. All GNN models are implemented and evaluated under the User Preference-aware Fake News Detection (UPFD) framework. The fake news detection problem is instantiated as a graph classification task under the UPFD framework.

Self-Supervised Music Analysis Self-Supervised Contrastive Learning of Music Spectrograms Dataset Songs on the Billboard Year End Hot 100 were collect

Esparto is a simple HTML and PDF document generator for Python. Its primary use is for generating shareable single page reports with content from popular analytics and data science libraries.

python_graphs This package is for computing graph representations of Python programs for machine learning applications. It includes the following modu

MaskCycleGAN-VC Unofficial PyTorch implementation of Kaneko et al.'s MaskCycleGAN-VC (2021) for non-parallel voice conversion. MaskCycleGAN-VC is the

30 Days Of Machine Learning Using Pytorch Objective of the repository is to learn and build machine learning models using Pytorch. List of Algorithms

简体中文 | English 并行语音合成 [TOC] 新进展 2021/04/20 合并 wavegan 分支到 main 主分支，删除 wavegan 分支！ 2021/04/13 创建 encoder 分支用于开发语音风格迁移模块！ 2021/04/13 softdtw 分支 支持使用 Sof

MILES Multilingual Lexical Simplifier Explore the docs » Read LSBert Paper · Report Bug · Request Feature About The Project MILES is a multilingual te

MevonAI - Speech Emotion Recognition

This Repostory contains the pretrained DTLN-aec model for real-time acoustic echo cancellation.

DeepSpeed is a deep learning optimization library that makes distributed training easy, efficient, and effective.

The PyTorch-Kaldi Speech Recognition Toolkit PyTorch-Kaldi is an open-source repository for developing state-of-the-art DNN/HMM speech recognition sys

BERT-pytorch Pytorch implementation of Google AI's 2018 BERT, with simple annotation BERT 2018 BERT: Pre-training of Deep Bidirectional Transformers f

About statsmodels statsmodels is a Python package that provides a complement to scipy for statistical computations including descriptive statistics an

PyMC3 is a Python package for Bayesian statistical modeling and Probabilistic Machine Learning focusing on advanced Markov chain Monte Carlo (MCMC) an

Validated, scalable, community developed variant calling, RNA-seq and small RNA analysis. You write a high level configuration file specifying your in

django-simple-history django-simple-history stores Django model state on every create/update/delete. This app supports the following combinations of D

An open source framework that provides a simple, universal API for building distributed applications. Ray is packaged with RLlib, a scalable reinforcement learning library, and Tune, a scalable hyperparameter tuning library.

Pydantic model support for Django ORM

erdantic is a simple tool for drawing entity relationship diagrams (ERDs) for Python data model classes. Diagrams are rendered using the venerable Graphviz library.

World on Rails Learning to drive from a world on rails Dian Chen, Vladlen Koltun, Philipp Krähenbühl, arXiv techical report (arXiv 2105.00636) This re

SentiLARE: Sentiment-Aware Language Representation Learning with Linguistic Knowledge Introduction SentiLARE is a sentiment-aware pre-trained language

ArviZ (pronounced "AR-vees") is a Python package for exploratory analysis of Bayesian models. Includes functions for posterior analysis, data storage, model checking, comparison and diagnostics

TorchFlare TorchFlare is a simple, beginner-friendly and an easy-to-use PyTorch Framework train your models without much effort. It provides an almost

Differentiable Model Compression via Pseudo Quantization Noise DiffQ performs differentiable quantization using pseudo quantization noise. It can auto

ReConsider ReConsider is a re-ranking model that re-ranks the top-K (passage, answer-span) predictions of an Open-Domain QA Model like DPR (Karpukhin

TorchShard is a lightweight engine for slicing a PyTorch tensor into parallel shards. It can reduce GPU memory and scale up the training when the model has massive linear layers (e.g., ViT, BERT and GPT) or huge classes (millions). It has the same API design as PyTorch.

SARS-CoV-2 processing requests Request execution of Galaxy SARS-CoV-2 variation analysis workflows on input data you provide. Prerequisites This autom

The implementation of paper CLIP4Clip: An Empirical Study of CLIP for End to End Video Clip Retrieval. CLIP4Clip is a video-text retrieval model based

End-to-End Coreference Resolution with Different Higher-Order Inference Methods This repository contains the implementation of the paper: Revealing th

PyKale is a PyTorch library for multimodal learning and transfer learning as well as deep learning and dimensionality reduction on graphs, images, texts, and videos. By adopting a unified pipeline-based API design, PyKale enforces standardization and minimalism, via reusing existing resources, reducing repetitions and redundancy, and recycling learning models across areas.

Repository on the collaborative IVADO medical imaging project between the Mila and NeuroPoly labs.

TalkNet 2 [WIP] TalkNet 2: Non-Autoregressive Depth-Wise Separable Convolutional Model for Speech Synthesis with Explicit Pitch and Duration Predictio

OCTIS : Optimizing and Comparing Topic Models is Simple! OCTIS (Optimizing and Comparing Topic models Is Simple) aims at training, analyzing and compa

mbrl-lib is a toolbox for facilitating development of Model-Based Reinforcement Learning algorithms. It provides easily interchangeable modeling and planning components, and a set of utility functions that allow writing model-based RL algorithms with only a few lines of code.

SMPLicit: Topology-aware Generative Model for Clothed People [Project] [arXiv] License Software Copyright License for non-commercial scientific resear

Generating Persona Consistent Dialogues by Exploiting Natural Language Inference Source code for RCDG model in AAAI20 Generating Persona Consistent Di

Sequence-to-sequence framework with a focus on Neural Machine Translation based on Apache MXNet

ForgeryNet: A Versatile Benchmark for Comprehensive Forgery Analysis ForgeryNet: A Versatile Benchmark for Comprehensive Forgery Analysis [arxiv|pdf|v

Gaphor is a UML and SysML modeling application written in Python. It is designed to be easy to use, while still being powerful. Gaphor implements a fully-compliant UML 2 data model, so it is much more than a picture drawing tool. You can use Gaphor to quickly visualize different aspects of a system as well as create complete, highly complex models.

GLM GLM is a General Language Model pretrained with an autoregressive blank-filling objective and can be finetuned on various natural language underst