Python Sequence Resources

LG-AI-Challenge-for-Plant-Classification Dacon에서 진행된 농업 환경 변화에 따른 작물 병해 진단 AI 경진대회 에 대한 코드입니다. (colab directory에 코드가 잘 정리 되어있습니다.) Requirements python

rich-msa A simple module to render colorful Multiple Sequence Alignment with rich in the terminal. 🔧 Installing Install the rich-msa package directly

Paper | Blog OFA is a unified multimodal pretrained model that unifies modalities (i.e., cross-modality, vision, language) and tasks (e.g., image gene

Behavior-Sequence-Transformer-Pytorch This is a pytorch implementation for the BST model from Alibaba https://arxiv.org/pdf/1905.06874.pdf This model

Description: ProtFeat is designed to extract the protein features by employing POSSUM and iFeature python-based tools. ProtFeat includes a total of 39

Fibonaaci Series Generating the Fibonacci sequence is a classic recursive proble

Official repository of OFA. Paper: Unifying Architectures, Tasks, and Modalities Through a Simple Sequence-to-Sequence Learning Framework

Minimal implementation of Decision Transformer: Reinforcement Learning via Sequence Modeling in PyTorch for mujoco control tasks in OpenAI gym

DNA sequence classification by Deep Neural Network: Project Overview worked on the DNA sequence classification problem where the input is the DNA sequ

Regression Transformer Codebase to experiment with a hybrid Transformer that combines conditional sequence generation with regression . Development se

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

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

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

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

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

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

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

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

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

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

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.

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

CFD Python Please cite as: Barba, Lorena A., and Forsyth, Gilbert F. (2018). CFD Python: the 12 steps to Navier-Stokes equations. Journal of Open Sour

Ejemplo Algoritmo Viterbi Ejemplo de un algoritmo Viterbi aplicado a modelo ocul

Forex Data Prediction via Recurrent Neural Network Deep Sequence Modeling Research Paper Our research paper can be viewed here Installation Clone the

msprime msprime is a population genetics simulator based on tskit. Msprime can simulate random ancestral histories for a sample of individuals (consis

Seq2seq Sequence to Sequence Learning with Keras Hi! You have just found Seq2Seq. Seq2Seq is a sequence to sequence learning add-on for the python dee

Self-Training for Neural Sequence Generation This repo includes instructions for running noisy self-training algorithms from the following paper: Revi

Sequence labeler This is a neural network sequence labeling system. Given a sequence of tokens, it will learn to assign labels to each token. Can be u

bistring The bistring library provides non-destructive versions of common string processing operations like normalization, case folding, and find/repl

This program analyzes a DNA sequence and outputs snippets of DNA that are likely to be protein-coding genes.

(intron I nterrogator and C lassifier) intronIC is a program that can be used to classify intron sequences as minor (U12-type) or major (U2-type), usi

Vdo & Img Conversion Tools This is a quick conversion tool made with python that can save you a lot of time. With this tool you can extract image sequ

Pango lineage information for German SARS-CoV-2 sequences This repository contains a join of the metadata and pango lineage tables of all German SARS-

mrsd: a toolkit to generate MR sequence diagrams mrsd is a Python toolkit to generate MR sequence diagrams, as shown below for the basic FLASH sequenc

script-SV-genotyping These are the scripts used for the project of ‘Assembly of a pan-genome for global cattle reveals missing sequence and novel stru

Nagisa is a python module for Japanese word segmentation/POS-tagging. It is designed to be a simple and easy-to-use tool. This tool has the following

Table of contents Introduction Using BARTpho with fairseq Using BARTpho with transformers Notes BARTpho: Pre-trained Sequence-to-Sequence Models for V

MT-VAE for Multimodal Human Motion Synthesis This is the code for ECCV 2018 paper MT-VAE: Learning Motion Transformations to Generate Multimodal Human

undirected-generation-dev This repo contains the source code of the models described in the following paper "Learning and Analyzing Generation Order f

SeqLike - flexible biological sequence objects in Python Introduction A single object API that makes working with biological sequences in Python more

PEGASUS library Pre-training with Extracted Gap-sentences for Abstractive SUmmarization Sequence-to-sequence models, or PEGASUS, uses self-supervised

ProphetNet-X This repo provides the code for reproducing the experiments in ProphetNet. In the paper, we propose a new pre-trained language model call

ObjSequenceViewer V0.5 A minimal, standalone viewer for 3D animations stored as stop-motion sequences of individual .obj mesh files. Installation: pip

CCasGNN A new framework, collaborative cascade prediction based on graph neural networks (CCasGNN) to jointly utilize the structural characteristics,

rapidnlp-datasets Data pipelines for both TensorFlow and PyTorch ! If you want to load public datasets, try: tensorflow/datasets huggingface/datasets

Simple, high-school-leveled sequence library written in Python

Transfer Learning for Text Classification with Tensorflow Tensorflow implementation of Semi-supervised Sequence Learning(https://arxiv.org/abs/1511.01

PyTorch-trainer-and-model-for-Sequence-Classification After cloning the repository, modify your training data so that the training data is a .csv file

BERTGEN This repository is the implementation of the paper "BERTGEN: Multi-task Generation through BERT" (https://arxiv.org/abs/2106.03484). The codeb

pytm: A Pythonic framework for threat modeling Introduction Traditional threat modeling too often comes late to the party, or sometimes not at all. In

Equi-RC Equivariant layers for RC-complement symmetry in DNA sequence data This is a repository that implements the layers as described in "Reverse-Co

FastTrees This repository contains the experimental code supporting the FastTrees paper by Bill Pung. Software Requirements Python 3.6, NLTK and PyTor

Sequence clustering and database creation using mmseqs, from local fasta files

trRosetta This package is a part of trRosetta protein structure prediction protocol developed in: Improved protein structure prediction using predicte

Trajectory Transformer Code release for Offline Reinforcement Learning as One Big Sequence Modeling Problem. Installation All python dependencies are

SeqGAN Requirements: Tensorflow r1.0.1 Python 2.7 CUDA 7.5+ (For GPU) Introduction Apply Generative Adversarial Nets to generating sequences of discre

Sequence Generation with GANs trained by Gradient Estimation Requirements: PyTorch v0.3 Python 3.6 CUDA 9.1 (For GPU) Origin The idea is from paper Se

Sequence to Sequence (seq2seq) Recurrent Neural Network (RNN) for Time Series Forecasting Note: You can find here the accompanying seq2seq RNN forecas

Keras implementation of a sequence to sequence model for time series prediction using an encoder-decoder architecture. I created this post to share a

Foreign Pronunciation Generator (English-Chinese) We provide a simple socket script for acquiring Chinese pronunciation of English words (phones in ai

hierarchical-transformer-1d Implementation of H-Transformer-1D, Hierarchical Attention for Sequence Learning using 🤗 transformers In Progress!! 2021.

q1pulse Pulse sequence builder and compiler for q1asm. q1pulse is a simple library to compile pulse sequence to q1asm, the assembly language of Qblox

VAC_CSLR This repo holds codes of the paper: Visual Alignment Constraint for Continuous Sign Language Recognition.(ICCV 2021) [paper] Prerequisites Th

Structured State Spaces for Sequence Modeling This repository provides implementations and experiments for the following papers. S4 Efficiently Modeli

Structured State Spaces for Sequence Modeling This repository provides implementations and experiments for the following papers. S4 Efficiently Modeli

T5X T5X is a modular, composable, research-friendly framework for high-performance, configurable, self-service training, evaluation, and inference of

A PyTorch Implementation of GGNN This is a PyTorch implementation of the Gated Graph Sequence Neural Networks (GGNN) as described in the paper Gated G

GDAP Code for Generating Disentangled Arguments with Prompts: A Simple Event Extraction Framework that Works Environment Python (verified: v3.8) CUDA

Convolutional Recurrent Neural Network This software implements the Convolutional Recurrent Neural Network (CRNN), a combination of CNN, RNN and CTC l

2021 CCF BDCI 全国信息检索挑战杯(CCIR-Cup) 智能人机交互自然语言理解赛道第二名解决方案 比赛网址: CCIR-Cup-智能人机交互自然语言理解 1.依赖环境： python==3.8 torch==1.7.1+cu110 numpy==1.19.2 transformers=

Discontinuous Grammar as a Foreign Language This repository includes the code of the sequence-to-sequence model for discontinuous constituent parsing

CRNN paper：An End-to-End Trainable Neural Network for Image-based Sequence Recognition and Its Application to Scene Text Recognition 1. create your ow

Fairseq(-py) is a sequence modeling toolkit that allows researchers and developers to train custom models for translation, summarization, language mod

Graph2SMILES A graph-to-sequence model for one-step retrosynthesis and reaction outcome prediction. 1. Environmental setup System requirements Ubuntu:

Source code for CAST: Crisis Domain Adaptation UsingSequence-to-sequenceTransformers (Paper, BibTeX, Accepted to ISCRAM 2021, CorePaper) Quick start D

Rescoring Sequence-to-Sequence Models for Text Line Recognition with CTC-Prefixes Setup virtualenv -p python3 venv source venv/bin/activate pip instal

Genomic ULMFiT This is an implementation of ULMFiT for genomics classification using Pytorch and Fastai. The model architecture used is based on the A

Neural Distance Embeddings for Biological Sequences Official implementation of Neural Distance Embeddings for Biological Sequences (NeuroSEED) in PyTo

🔧 What is it? Wrench is a benchmark platform containing diverse weak supervision tasks. It also provides a common and easy framework for development

Lingvo is a framework for building neural networks in Tensorflow, particularly sequence models.

TrellisNet for Sequence Modeling This repository contains the experiments done in paper Trellis Networks for Sequence Modeling by Shaojie Bai, J. Zico

This is a fork of Fairseq(-py) with implementations of the following models: Pervasive Attention - 2D Convolutional Neural Networks for Sequence-to-Se

transducer A Fast Sequence Transducer Implementation with PyTorch Bindings. The corresponding publication is Sequence Transduction with Recurrent Neur

Sequence Modeling Benchmarks and Temporal Convolutional Networks (TCN) This repository contains the experiments done in the work An Empirical Evaluati

SCINet This is the original PyTorch implementation of the following work: Time Series is a Special Sequence: Forecasting with Sample Convolution and I

Seq2Seq in PyTorch This is a complete suite for training sequence-to-sequence models in PyTorch. It consists of several models and code to both train

Sequence to Sequence models with PyTorch This repository contains implementations of Sequence to Sequence (Seq2Seq) models in PyTorch At present it ha

SupCL-Seq 📖 Supervised Contrastive Learning for Downstream Optimized Sequence representations (SupCS-Seq) accepted to be published in EMNLP 2021, ext

Selene is a Python library and command line interface for training deep neural networks from biological sequence data such as genomes.

Code for the paper: Sequence-to-Sequence Learning with Latent Neural Grammars

Trajectory Transformer Code release for Reinforcement Learning as One Big Sequence Modeling Problem. Installation All python dependencies are in envir

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.

Pytorch-NLU，一个中文文本分类、序列标注工具包，支持中文长文本、短文本的多类、多标签分类任务，支持中文命名实体识别、词性标注、分词等序列标注任务。 Ptorch NLU, a Chinese text classification and sequence annotation toolkit, supports multi class and multi label classification tasks of Chinese long text and short text, and supports sequence annotation tasks such as Chinese named entity recognition, part of speech tagging and word segmentation.

DeepConsensus DeepConsensus uses gap-aware sequence transformers to correct errors in Pacific Biosciences (PacBio) Circular Consensus Sequencing (CCS)

Template-Based NER Source Code For Template-Based Named Entity Recognition Using BART Training Training train.py Inference inference.py Corpus ATIS (h

Seq2Seq in PyTorch This is a complete suite for training sequence-to-sequence models in PyTorch. It consists of several models and code to both train

Token Shift GPT Implementation of Token Shift GPT - An autoregressive model that relies solely on shifting along the sequence dimension and feedforwar

LM-LSTM-CRF Check Our New NER Toolkit 🚀 🚀 🚀 Inference: LightNER: inference w. models pre-trained / trained w. any following tools, efficiently. Tra