Python Self-critical-sequence-training Resources

Official PyTorch implementation of the paper "Likelihood Training of Schrödinger Bridge using Forward-Backward SDEs Theory (SB-FBSDE)" which introduces a new class of deep generative models that generalizes score-based models to fully nonlinear forward and backward diffusions.

An Efficient Library for Training Deep Models This repository provides an efficient PyTorch-based library for training deep models. Installation Make

Speech Resynthesis from Discrete Disentangled Self-Supervised Representations Implementation of the method described in the Speech Resynthesis from Di

Classification using Deep Learning Requirements PyTorch version = 1.9.1+cu111 Python version = 3.8.10 PyTorch-Lightning version = 1.4.9 Huggingface

Welcome to AirSim AirSim is a simulator for drones, cars and more, built on Unreal Engine (we now also have an experimental Unity release). It is open

A Multi-Tool with 30+Options.

En- and decrypting text-messages by creating a key with of the fibonacci-sequence. This key helps to create mathematical functions, whose zeros should generates the encrypted message.

Temporal Alignment Prediction for Supervised Representation Learning and Few-Shot Sequence Classification Introduction. This package includes the pyth

Human-Segmentation-PyTorch Human segmentation models, training/inference code, and trained weights, implemented in PyTorch. Supported networks UNet: b

What's this? A simple interactive CLI wrapper around openssl to make self-signin

This project is a convolutional neural network (CNN) that analyzes self-generated images in a variety of languages to find etymological similarities. Specifically, the goal is to prove that computer vision can be used to identify cognates known to exist, and perhaps lead linguists to evidence of unknown cognates.

Data from "Datamodels: Predicting Predictions with Training Data" Here we provid

Iterative refinement graph neural network for antibody sequence-structure co-des

ADE20k Semantic segmentation with MAE Getting started Install the mmsegmentation

Advanced-Machine-Learning This repository contains the code for the project Real

Training-a-deep-learning-model-on-the-noisy-CIFAR-dataset This repository contai

neural-modular Simple codebase for flexible neural net training. Allows for seamless exchange of models, dataset, and optimizers. Uses hydra for confi

A transformer that does not hog your GPU memory This is an early in-development codebase: if you want a stable and documented hivemind codebase, look

DirectCLR DirectCLR is a simple contrastive learning model for visual representation learning. It does not require a trainable projector as SimCLR. It

This repository contains the raw dataset used in NHNet [1] for the task of News Story Headline Generation. The code of data processing and training is available under Tensorflow Models - NHNet.

BLIP: Bootstrapping Language-Image Pre-training for Unified Vision-Language Understanding and Generation

[ICLR 2022] Deep Ensembling with No Overhead for either Training or Testing: The All-Round Blessings of Dynamic Sparsity by Shiwei Liu, Tianlong Chen, Zahra Atashgahi, Xiaohan Chen, Ghada Sokar, Elena Mocanu, Mykola Pechenizkiy, Zhangyang Wang, Decebal Constantin Mocanu

Diaformer Diaformer: Automatic Diagnosis via Symptoms Sequence Generation (AAAI 2022) Diaformer is an efficient model for automatic diagnosis via symp

Variational DiffWave Training DiffWave using variational method from Variational Diffusion Models. Quick Start python train_distributed.py discrete_10

NANSY: Unofficial Pytorch Implementation of Neural Analysis and Synthesis: Reconstructing Speech from Self-Supervised Representations Notice Papers' D

BaseCls BaseCls 是一个基于 MegEngine 的预训练模型库，帮助大家挑选或训练出更适合自己科研或者业务的模型结构。 文档地址：https://basecls.readthedocs.io 安装 安装环境 BaseCls 需要 Python = 3.6。 BaseCls 依赖 M

Self-supervised learning Self-supervised learning algorithms provide a way to train Deep Neural Networks in an unsupervised way using contrastive loss

CAST: Character labeling in Animation using Self-supervision by Tracking (Published as a conference paper at EuroGraphics 2022) Note: The CAST paper c

Using Self-Supervised Pretext Tasks for Active Learning - Official Pytorch Implementation Experiment Setting: CIFAR10 (downloaded and saved in ./DATA

NaturalCC NaturalCC is a sequence modeling toolkit that allows researchers and developers to train custom models for many software engineering tasks,

Self-Blind-VSR Paper | Discussion Self-Supervised Deep Blind Video Super-Resolution By Haoran Bai and Jinshan Pan Abstract Existing deep learning-base

JASS: Japanese-specific Sequence to Sequence Pre-training for Neural Machine Translation This the repository for this paper. Find extensions of this w

WPPNets: Unsupervised CNN Training with Wasserstein Patch Priors for Image Superresolution This code belongs to the paper [1] available at https://arx

LongScientificFormer For encoding a text longer than 512 tokens, for example 800. Set max_pos to 800 during both preprocessing and training. Some code

Visual Representation Learning with Self-Supervised Attention for Low-Label High-Data Regime Created by Prarthana Bhattacharyya. Disclaimer: This is n

ReLSO Improved Fitness Optimization Landscapes for Sequence Design Description Citation How to run Training models Original data source Description In

Using Attention in HRL Framework for training options with different attention mechanism and using them to solve downstream tasks. Requirements GPU re

Identifying a Training-Set Attack’s Target Using Renormalized Influence Estimation By: Zayd Hammoudeh and Daniel Lowd Paper: Arxiv Preprint Coming soo

Post-training Quantization for Neural Networks with Provable Guarantees Authors: Jinjie Zhang ([email protected]), Yixuan Zhou ([email protected]) and Ray

Shahzain SelfBot This tool is created by Shahzain and is one of the best self bots out there! Features Token Destroyer! Server Nuker(50-100 Bans Per S

Innocent-bot A Discord client self-bot for destroying, nuking and causing mischi

SAS: Self-Augmentation Strategy for Language Model Pre-training This repository

SWAG: Supervised Weakly from hashtAGs This repository contains SWAG models from the paper Revisiting Weakly Supervised Pre-Training of Visual Percepti

Sequence-Labeling-Early-Exit Code for ACL 2021 paper: Accelerating BERT Inference for Sequence Labeling via Early-Exit Requirement: Please refer to re

CST Code release for "Cycle Self-Training for Domain Adaptation" (NeurIPS 2021) Prerequisites torch=1.7.0 torchvision qpsolvers numpy prettytable tqd

Learning Time-Critical Responses for Interactive Character Control Abstract This code implements the paper Learning Time-Critical Responses for Intera

Self-supervised learning (SSL) is a method of machine learning. It learns from unlabeled sample data. It can be regarded as an intermediate form between supervised and unsupervised learning.

pyspark_sam This repo hosts my code for the article "Analyze Big Sequence Alignm

Khue's Homelab Current status: ALPHA This project utilizes Infrastructure as Code to automate provisioning, operating, and updating self-hosted servic

CLIP [Blog] [Paper] [Model Card] [Colab] CLIP (Contrastive Language-Image Pre-Training) is a neural network trained on a variety of (image, text) pair

cell_counting_v2 The repository includes the code for training cell counting applications. (Keras + Tensorflow) Dataset can be downloaded here : http:

self-driving-car In this repository I will share the source code of all the projects of Udacity Self-Driving Car Engineer Nanodegree. Hope this might

Segmentation Training Pipeline This package is a part of Musket ML framework. Reasons to use Segmentation Pipeline Segmentation Pipeline was developed

A Memory Tracer For PyTorch OOM is a nightmare for PyTorch users. However, most

First steps with Python in Life Sciences This course material is part of the "First Steps with Python in Life Science" three-day course of SIB-trainin

Collapse by Conditioning: Training Class-conditional GANs with Limited Data Moha

ESGD-M - A stochastic non-convex second order optimizer, suitable for training deep learning models, for PyTorch

The mod is fkn 10y old and has'nt a self-updater. To use it just run the exec, wait some seconds, and it will run the new modsk

HistoSeg : Quick attention with multi-loss function for multi-structure segmentation in digital histology images Histological Image Segmentation This

BioPy is a collection (in-progress) of biologically-inspired algorithms written in Python. Some of the algorithms included are mor

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

Flower-timeout Repo for investigation of timeouts that happens with prolonged training on clients. This repository is meant purely for demonstration o

Self-Supervised Anomaly Segmentation Intorduction This is a PyToch implementation of A Novel Self-supervised Learning Task Designed for Anomaly Segmen

GitHub-Actions-Docker-training Training exercise repository for GitHub Actions using a docker base. This repository should be cloned and used for trai

Transformer-in-Vision Recent Transformer-based CV and related works. Welcome to comment/contribute! Keep updated. Resource SCENIC: A JAX Library for C

awesome-fast-attention A curated list of efficient attention modules

Circuit Training: An open-source framework for generating chip floor plans with distributed deep reinforcement learning. Circuit Training is an open-s

Meta Self-Learning for Multi-Source Domain Adaptation: A Benchmark Project | Arxiv | YouTube | | Abstract In recent years, deep learning-based methods

X-VLM: learning multi-grained vision language alignments Multi-Grained Vision Language Pre-Training: Aligning Texts with Visual Concepts. Yan Zeng, Xi

ColossalAI-Examples This repository contains examples of training models with Co

Fuzzware Fuzzware is a project for automated, self-configuring fuzzing of firmware images. The idea of this project is to configure the memory ranges

A novel Engagement Detection with Multi-Task Training (ED-MTT) system which minimizes MSE and triplet loss together to determine the engagement level of students in an e-learning environment.

TiP-Adapter: Training-free CLIP-Adapter for Better Vision-Language Modeling This is the official code release for the paper 'TiP-Adapter: Training-fre

VIOLET: End-to-End Video-Language Transformers with Masked Visual-token Modeling A PyTorch implementation of VIOLET Overview VIOLET is an implementati

ffcv ImageNet Training A minimal, single-file PyTorch ImageNet training script designed for hackability. Run train_imagenet.py to get... ...high accur

ParaGen is a PyTorch deep learning framework for parallel sequence generation. Apart from sequence generation, ParaGen also enhances various NLP tasks, including sequence-level classification, extraction and generation.

This repository contains the implementation for the paper: No-Reference Image Quality Assessment via Transformers, Relative Ranking, and Self-Consiste

RefinerViT This repo is the official implementation of "Refiner: Refining Self-attention for Vision Transformers". The repo is build on top of timm an

An official PyTorch Implementation of Boundary-aware Self-supervised Learning for Video Scene Segmentation (BaSSL)

Moshpit SGD: Communication-Efficient Decentralized Training on Heterogeneous Unreliable Devices This repository contains the official PyTorch implemen

Implementations for the ICLR-2021 paper: SEED: Self-supervised Distillation For Visual Representation.

Pose Detection Project Description: Human pose estimation from video plays a critical role in various applications such as quantifying physical exerci

This is the implementation of "Training deep neural networks via direct loss minimization" published at ICML 2016 in PyTorch. The implementation targe

Pianote Pianote is an application that helps musicians practice piano ear traini

NeWT: Natural World Tasks This repository contains resources for working with the NeWT dataset. ❗ At this time the binary tasks are not publicly avail

Implementing SYNTHESIZER: Rethinking Self-Attention in Transformer Models using Pytorch Reference Paper URL Author: Yi Tay, Dara Bahri, Donald Metzler

Monitor deep learning model training and hardware usage from mobile. 🔥 Features Monitor running experiments from mobile phone (or laptop) Monitor har

Action Recognition for Self-Driving Cars This repo contains the codes for the 2021 Fall semester project "Action Recognition for Self-Driving Cars" at

SSMNR | Self-Supervised Methods for Noise Removal Image denoising is the task of removing noise from an image, which can be formulated as the task of

Tube Self-Attention Network (TSA-Net) This repository contains the PyTorch implementation for paper TSA-Net: Tube Self-Attention Network for Action Qu

BRATS 2021 Solution For Segmentation Task This repo contains the supported pytorch code and configuration files to reproduce 3D medical image segmenta

Morpheus-Deblend This repo generates the training data and the model for Morpheus-Deblend. This is the active development repo for the project and as

SimReg: A Simple Regression Based Framework for Self-supervised Knowledge Distillation Source code for the paper "SimReg: Regression as a Simple Yet E

ELSA: Enhanced Local Self-Attention for Vision Transformer By Jingkai Zhou, Pich

Algorithms Classic algorithms including Fizz Buzz, Bubble Sort, the Fibonacci Sequence, a Sudoku solver, and more. Algorithm Complexity Time and Space

EEG-Oriented Self-Supervised Learning and Cluster-Aware Adaptation This repository provides a tensorflow implementation of a submitted paper: EEG-Orie

Semi-Supervised Learning with Multi-Head Co-Training (PyTorch) Abstract Co-training, extended from self-training, is one of the frameworks for semi-su

Self-supervised Structure-sensitive Learning (SSL) Ke Gong, Xiaodan Liang, Xiaohui Shen, Liang Lin, "Look into Person: Self-supervised Structure-sensi

Pyasmtools - looking at the python bytecode for fun and profit. The pyasmtools library is made up of two parts A python bytecode disassembler . See Py

ff-neural-network A Python module for the generation and training of an entry-level feedforward neural network. This repository serves as a repurposin