Python Sequence-tagging 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

Feature_CRF_AE Feature_CRF_AE provides a implementation of Bridging Pre-trained Language Models and Hand-crafted Features for Unsupervised POS Tagging

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

nlabel is a library for generating, storing and retrieving tagging information and embedding vectors from various nlp libraries through a unified interface.

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

TweebankNLP This repo contains the new Tweebank-NER dataset and off-the-shelf Twitter-Stanza pipeline for state-of-the-art Tweet NLP, as described 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

TweebankNLP This repo contains the new Tweebank-NER dataset and Twitter-Stanza p

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.

openalex-concept-tagging This repository contains all of the code for getting the concept tagger up and running. To learn more about where this model

NLP: SLU tagging

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

NLP-Models-Tensorflow, Gathers machine learning and tensorflow deep learning models for NLP problems, code simplify inside Jupyter Notebooks 100%. Tab

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

taganomaly Anomaly detection labeling tool, specifically for multiple time series (one time series per category). Taganomaly is a tool for creating la

Taguette A spin on the phrase "tag it!", Taguette is a free and open source qualitative research tool that allows users to: Import PDFs, Word Docs (.d

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

spacy-streamlit: spaCy building blocks for Streamlit apps This package contains utilities for visualizing spaCy models and building interactive spaCy-

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

Part of Speech Tagging using Hidden Markov Model (HMM) POS Tagger and Brill Tagger In this project, our aim is to tune, compare, and contrast the perf

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

Character Transformations for Non-Autoregressive GEC Tagging Milan Straka, Jakub Náplava, Jana Straková Charles University Faculty of Mathematics and

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

PSLA: Improving Audio Tagging with Pretraining, Sampling, Labeling, and Aggregation Introduction Getting Started FSD50K Recipe AudioSet Recipe Label E

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

PaSST: Efficient Training of Audio Transformers with Patchout This is the implementation for Efficient Training of Audio Transformers with Patchout Pa

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

max_tweeted_word This code is for a bot which will find a Twitter user's most tweeted word and tweet that word, tagging said user The program uses twe

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

Tag Machine A little Python application to auto tag your photos with the power of machine learning. Report a bug or request a feature Table of Content

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

IRIS NLP SYSTEM A NLP program: tokenize method, PoS Tagging with deep learning Report Bug · Request Feature Table of Contents About The Project Built

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:

Amazon Forest Computer Vision Satellite Image tagging code using PyTorch / Keras Here is a sample of images we had to work with Source: https://www.ka

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.