213 Repositories
Python sequence-labeling Libraries
Code for Generating Disentangled Arguments with Prompts: A Simple Event Extraction Framework that Works
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 (CRNN) for image-based sequence recognition.
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参赛解决方案
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=
This repository includes the code of the sequence-to-sequence model for discontinuous constituent parsing described in paper Discontinuous Grammar as a Foreign Language.
Discontinuous Grammar as a Foreign Language This repository includes the code of the sequence-to-sequence model for discontinuous constituent parsing
An End-to-End Trainable Neural Network for Image-based Sequence Recognition and Its Application to Scene Text Recognition
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
Code/data of the paper "Hand-Object Contact Prediction via Motion-Based Pseudo-Labeling and Guided Progressive Label Correction" (BMVC2021)
Hand-Object Contact Prediction (BMVC2021) This repository contains the code and data for the paper "Hand-Object Contact Prediction via Motion-Based Ps
This is a tool to help people to make a bot for labelling images for machine learning projects.
labeller_images_python_telegramBOT This is a bot to help collect data for any machine learning project. It was developed using the python-telegram-bot
Finetuner allows one to tune the weights of any deep neural network for better embeddings on search tasks
Finetuner allows one to tune the weights of any deep neural network for better embeddings on search tasks
TagLab: an image segmentation tool oriented to marine data analysis
TagLab: an image segmentation tool oriented to marine data analysis TagLab was created to support the activity of annotation and extraction of statist
Visage Differentiation is a GUI application for outlining and labeling the visages in an image.
Visage Differentiation Visage Differentiation is a GUI application for outlining and labeling the visages in an image. The main functionality is provi
Facebook AI Research Sequence-to-Sequence Toolkit written in Python.
Fairseq(-py) is a sequence modeling toolkit that allows researchers and developers to train custom models for translation, summarization, language mod
A graph-to-sequence model for one-step retrosynthesis and reaction outcome prediction.
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 Using Sequence-to-sequence Transformers (Accepted to ISCRAM 2021, CorePaper).
Source code for CAST: Crisis Domain Adaptation UsingSequence-to-sequenceTransformers (Paper, BibTeX, Accepted to ISCRAM 2021, CorePaper) Quick start D
Repository sharing code and the model for the paper "Rescoring Sequence-to-Sequence Models for Text Line Recognition with CTC-Prefixes"
Rescoring Sequence-to-Sequence Models for Text Line Recognition with CTC-Prefixes Setup virtualenv -p python3 venv source venv/bin/activate pip instal
ULMFiT for Genomic Sequence Data
Genomic ULMFiT This is an implementation of ULMFiT for genomics classification using Pytorch and Fastai. The model architecture used is based on the A
Implementation of Neural Distance Embeddings for Biological Sequences (NeuroSEED) in PyTorch
Neural Distance Embeddings for Biological Sequences Official implementation of Neural Distance Embeddings for Biological Sequences (NeuroSEED) in PyTo
WRENCH: Weak supeRvision bENCHmark
🔧 What is it? Wrench is a benchmark platform containing diverse weak supervision tasks. It also provides a common and easy framework for development
GLaRA: Graph-based Labeling Rule Augmentation for Weakly Supervised Named Entity Recognition
GLaRA: Graph-based Labeling Rule Augmentation for Weakly Supervised Named Entity Recognition
Lingvo is a framework for building neural networks in Tensorflow, particularly sequence models.
Lingvo is a framework for building neural networks in Tensorflow, particularly sequence models.
[ICLR'19] Trellis Networks for Sequence Modeling
TrellisNet for Sequence Modeling This repository contains the experiments done in paper Trellis Networks for Sequence Modeling by Shaojie Bai, J. Zico
Pervasive Attention: 2D Convolutional Networks for Sequence-to-Sequence Prediction
This is a fork of Fairseq(-py) with implementations of the following models: Pervasive Attention - 2D Convolutional Neural Networks for Sequence-to-Se
A Fast Sequence Transducer Implementation with PyTorch Bindings
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
Sequence Modeling Benchmarks and Temporal Convolutional Networks (TCN) This repository contains the experiments done in the work An Empirical Evaluati
The GitHub repository for the paper: “Time Series is a Special Sequence: Forecasting with Sample Convolution and Interaction“.
SCINet This is the original PyTorch implementation of the following work: Time Series is a Special Sequence: Forecasting with Sample Convolution and I
Labelling platform for text using distant supervision
With DataQA, you can label unstructured text documents using rule-based distant supervision.
Sequence-to-Sequence learning using PyTorch
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
Sequence to Sequence models with PyTorch This repository contains implementations of Sequence to Sequence (Seq2Seq) models in PyTorch At present it ha
Supervised Contrastive Learning for Downstream Optimized Sequence Representations
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.
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
Code for the paper: Sequence-to-Sequence Learning with Latent Neural Grammars
✨Rubrix is a production-ready Python framework for exploring, annotating, and managing data in NLP projects.
✨A Python framework to explore, label, and monitor data for NLP projects
Code for the paper "Reinforcement Learning as One Big Sequence Modeling Problem"
Trajectory Transformer Code release for Reinforcement Learning as One Big Sequence Modeling Problem. Installation All python dependencies are in envir
CLabel is a terminal-based cluster labeling tool that allows you to explore text data interactively and label clusters based on reviewing that data.
CLabel is a terminal-based cluster labeling tool that allows you to explore text data interactively and label clusters based on reviewing that
MWPToolkit is a PyTorch-based toolkit for Math Word Problem (MWP) solving.
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.
A data annotation pipeline to generate high-quality, large-scale speech datasets with machine pre-labeling and fully manual auditing.
About This repository provides data and code for the paper: Scalable Data Annotation Pipeline for High-Quality Large Speech Datasets Development (subm
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.
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 uses gap-aware sequence transformers to correct errors in Pacific Biosciences (PacBio) Circular Consensus Sequencing (CCS) data.
DeepConsensus DeepConsensus uses gap-aware sequence transformers to correct errors in Pacific Biosciences (PacBio) Circular Consensus Sequencing (CCS)
Source Code For Template-Based Named Entity Recognition Using BART
Template-Based NER Source Code For Template-Based Named Entity Recognition Using BART Training Training train.py Inference inference.py Corpus ATIS (h
Sequence-to-Sequence learning using PyTorch
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
Implementation of Token Shift GPT - An autoregressive model that solely relies on shifting the sequence space for mixing
Token Shift GPT Implementation of Token Shift GPT - An autoregressive model that relies solely on shifting along the sequence dimension and feedforwar
Experiments on Flood Segmentation on Sentinel-1 SAR Imagery with Cyclical Pseudo Labeling and Noisy Student Training
Flood Detection Challenge This repository contains code for our submission to the ETCI 2021 Competition on Flood Detection (Winning Solution #2). Acco
Image transformations designed for Scene Text Recognition (STR) data augmentation. Published at ICCV 2021 Workshop on Interactive Labeling and Data Augmentation for Vision.
Data Augmentation for Scene Text Recognition (ICCV 2021 Workshop) (Pronounced as "strog") Paper Arxiv Why it matters? Scene Text Recognition (STR) req
Empower Sequence Labeling with Task-Aware Language Model
LM-LSTM-CRF Check Our New NER Toolkit 🚀 🚀 🚀 Inference: LightNER: inference w. models pre-trained / trained w. any following tools, efficiently. Tra
A graphical Semi-automatic annotation tool based on labelImg and Yolov5
💕YOLOV5 semi-automatic annotation tool (Based on labelImg)
Stacked Hourglass Network with a Multi-level Attention Mechanism: Where to Look for Intervertebral Disc Labeling
⚠️ A more recent and actively-maintained version of this code is available in ivadomed Stacked Hourglass Network with a Multi-level Attention Mech
Unofficial pytorch implementation for Self-critical Sequence Training for Image Captioning. and others.
An Image Captioning codebase This is a codebase for image captioning research. It supports: Self critical training from Self-critical Sequence Trainin
PyTorch implementation for Stochastic Fine-grained Labeling of Multi-state Sign Glosses for Continuous Sign Language Recognition.
Stochastic CSLR This is the PyTorch implementation for the ECCV 2020 paper: Stochastic Fine-grained Labeling of Multi-state Sign Glosses for Continuou
LightSeq is a high performance training and inference library for sequence processing and generation implemented in CUDA
LightSeq: A High Performance Library for Sequence Processing and Generation
An implementation for `Text2Event: Controllable Sequence-to-Structure Generation for End-to-end Event Extraction`
Text2Event An implementation for Text2Event: Controllable Sequence-to-Structure Generation for End-to-end Event Extraction Please contact Yaojie Lu (@
Code for paper "ASAP-Net: Attention and Structure Aware Point Cloud Sequence Segmentation"
ASAP-Net This project implements ASAP-Net of paper ASAP-Net: Attention and Structure Aware Point Cloud Sequence Segmentation (BMVC2020). Overview We i
An official implementation of the paper Exploring Sequence Feature Alignment for Domain Adaptive Detection Transformers
Sequence Feature Alignment (SFA) By Wen Wang, Yang Cao, Jing Zhang, Fengxiang He, Zheng-jun Zha, Yonggang Wen, and Dacheng Tao This repository is an o
MASS: Masked Sequence to Sequence Pre-training for Language Generation
MASS: Masked Sequence to Sequence Pre-training for Language Generation
A PyTorch Implementation of Gated Graph Sequence Neural Networks (GGNN)
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
Sequence modeling benchmarks and temporal convolutional networks
Sequence Modeling Benchmarks and Temporal Convolutional Networks (TCN) This repository contains the experiments done in the work An Empirical Evaluati
LogDeep is an open source deeplearning-based log analysis toolkit for automated anomaly detection.
LogDeep is an open source deeplearning-based log analysis toolkit for automated anomaly detection.
Implementation of H-Transformer-1D, Hierarchical Attention for Sequence Learning
H-Transformer-1D Implementation of H-Transformer-1D, Transformer using hierarchical Attention for sequence learning with subquadratic costs. For now,
Rubrix is a free and open-source tool for exploring and iterating on data for artificial intelligence projects.
Open-source tool for exploring, labeling, and monitoring data for AI projects
A Fast Sequence Transducer Implementation with PyTorch Bindings
transducer A Fast Sequence Transducer Implementation with PyTorch Bindings. The corresponding publication is Sequence Transduction with Recurrent Neur
Pervasive Attention: 2D Convolutional Networks for Sequence-to-Sequence Prediction
This is a fork of Fairseq(-py) with implementations of the following models: Pervasive Attention - 2D Convolutional Neural Networks for Sequence-to-Se
[ICLR'19] Trellis Networks for Sequence Modeling
TrellisNet for Sequence Modeling This repository contains the experiments done in paper Trellis Networks for Sequence Modeling by Shaojie Bai, J. Zico
A highly sophisticated sequence-to-sequence model for code generation
CoderX A proof-of-concept AI system by Graham Neubig (June 30, 2021). About CoderX CoderX is a retrieval-based code generation AI system reminiscent o
Code for the RA-L (ICRA) 2021 paper "SeqNet: Learning Descriptors for Sequence-Based Hierarchical Place Recognition"
SeqNet: Learning Descriptors for Sequence-Based Hierarchical Place Recognition [ArXiv+Supplementary] [IEEE Xplore RA-L 2021] [ICRA 2021 YouTube Video]
Sequence model architectures from scratch in PyTorch
This repository implements a variety of sequence model architectures from scratch in PyTorch. Effort has been put to make the code well structured so that it can serve as learning material. The training loop implements the learner design pattern from fast.ai in pure PyTorch, with access to the loop provided through callbacks. Detailed logging and graphs are also provided with python logging and wandb. Additional implementations will be added.
DeepLab2: A TensorFlow Library for Deep Labeling
DeepLab2 is a TensorFlow library for deep labeling, aiming to provide a unified and state-of-the-art TensorFlow codebase for dense pixel labeling tasks.
Markup is an online annotation tool that can be used to transform unstructured documents into structured formats for NLP and ML tasks, such as named-entity recognition. Markup learns as you annotate in order to predict and suggest complex annotations. Markup also provides integrated access to existing and custom ontologies, enabling the prediction and suggestion of ontology mappings based on the text you're annotating.
Markup is an online annotation tool that can be used to transform unstructured documents into structured formats for NLP and ML tasks, such as named-entity recognition. Markup learns as you annotate in order to predict and suggest complex annotations. Markup also provides integrated access to existing and custom ontologies, enabling the prediction and suggestion of ontology mappings based on the text you're annotating.
Pytorch implementation of the paper SPICE: Semantic Pseudo-labeling for Image Clustering
SPICE: Semantic Pseudo-labeling for Image Clustering By Chuang Niu and Ge Wang This is a Pytorch implementation of the paper. (In updating) SOTA on 5
Unifying Cross-Lingual Semantic Role Labeling with Heterogeneous Linguistic Resources (NAACL-2021).
Unifying Cross-Lingual Semantic Role Labeling with Heterogeneous Linguistic Resources Description This is the repository for the paper Unifying Cross-
Code for our paper "Transfer Learning for Sequence Generation: from Single-source to Multi-source" in ACL 2021.
TRICE: a task-agnostic transferring framework for multi-source sequence generation This is the source code of our work Transfer Learning for Sequence
code for our paper "Source Data-absent Unsupervised Domain Adaptation through Hypothesis Transfer and Labeling Transfer"
SHOT++ Code for our TPAMI submission "Source Data-absent Unsupervised Domain Adaptation through Hypothesis Transfer and Labeling Transfer" that is ext
Official codebase for Decision Transformer: Reinforcement Learning via Sequence Modeling.
Decision Transformer Lili Chen*, Kevin Lu*, Aravind Rajeswaran, Kimin Lee, Aditya Grover, Michael Laskin, Pieter Abbeel, Aravind Srinivas†, and Igor M
You Only 👀 One Sequence
You Only 👀 One Sequence TL;DR: We study the transferability of the vanilla ViT pre-trained on mid-sized ImageNet-1k to the more challenging COCO obje
Code for the ACL2021 paper "Lexicon Enhanced Chinese Sequence Labelling Using BERT Adapter"
Lexicon Enhanced Chinese Sequence Labeling Using BERT Adapter Code and checkpoints for the ACL2021 paper "Lexicon Enhanced Chinese Sequence Labelling
Simultaneous NMT/MMT framework in PyTorch
This repository includes the codes, the experiment configurations and the scripts to prepare/download data for the Simultaneous Machine Translation wi
CAUSE: Causality from AttribUtions on Sequence of Events
CAUSE: Causality from AttribUtions on Sequence of Events
tsai is an open-source deep learning package built on top of Pytorch & fastai focused on state-of-the-art techniques for time series classification, regression and forecasting.
Time series Timeseries Deep Learning Pytorch fastai - State-of-the-art Deep Learning with Time Series and Sequences in Pytorch / fastai
Sequence-to-Sequence Framework in PyTorch
nmtpytorch allows training of various end-to-end neural architectures including but not limited to neural machine translation, image captioning and au
Facebook AI Research Sequence-to-Sequence Toolkit written in Python.
Fairseq(-py) is a sequence modeling toolkit that allows researchers and developers to train custom models for translation, summarization, language mod
LightSeq: A High-Performance Inference Library for Sequence Processing and Generation
LightSeq is a high performance inference library for sequence processing and generation implemented in CUDA. It enables highly efficient computation of modern NLP models such as BERT, GPT2, Transformer, etc. It is therefore best useful for Machine Translation, Text Generation, Dialog, Language Modelling, and other related tasks using these models.
One Stop Anomaly Shop: Anomaly detection using two-phase approach: (a) pre-labeling using statistics, Natural Language Processing and static rules; (b) anomaly scoring using supervised and unsupervised machine learning.
One Stop Anomaly Shop (OSAS) Quick start guide Step 1: Get/build the docker image Option 1: Use precompiled image (might not reflect latest changes):
Task-based datasets, preprocessing, and evaluation for sequence models.
SeqIO: Task-based datasets, preprocessing, and evaluation for sequence models. SeqIO is a library for processing sequential data to be fed into downst
Sequence-to-sequence framework with a focus on Neural Machine Translation based on Apache MXNet
Sequence-to-sequence framework with a focus on Neural Machine Translation based on Apache MXNet
Weakly supervised medical named entity classification
Trove Trove is a research framework for building weakly supervised (bio)medical named entity recognition (NER) and other entity attribute classifiers
Diffgram - Supervised Learning Data Platform
Data Annotation, Data Labeling, Annotation Tooling, Training Data for Machine Learning
CLASP - Contrastive Language-Aminoacid Sequence Pretraining
CLASP - Contrastive Language-Aminoacid Sequence Pretraining Repository for creating models pretrained on language and aminoacid sequences similar to C
Combining Automatic Labelers and Expert Annotations for Accurate Radiology Report Labeling Using BERT
CheXbert: Combining Automatic Labelers and Expert Annotations for Accurate Radiology Report Labeling Using BERT CheXbert is an accurate, automated dee
[CVPR 2021] Rethinking Semantic Segmentation from a Sequence-to-Sequence Perspective with Transformers
[CVPR 2021] Rethinking Semantic Segmentation from a Sequence-to-Sequence Perspective with Transformers
An efficient and effective learning to rank algorithm by mining information across ranking candidates. This repository contains the tensorflow implementation of SERank model. The code is developed based on TF-Ranking.
SERank An efficient and effective learning to rank algorithm by mining information across ranking candidates. This repository contains the tensorflow
Understanding and Improving Encoder Layer Fusion in Sequence-to-Sequence Learning (ICLR 2021)
Understanding and Improving Encoder Layer Fusion in Sequence-to-Sequence Learning (ICLR 2021) Citation Please cite as: @inproceedings{liu2020understan
Convolutional Recurrent Neural Networks(CRNN) for Scene Text Recognition
CRNN_Tensorflow This is a TensorFlow implementation of a Deep Neural Network for scene text recognition. It is mainly based on the paper "An End-to-En
a Deep Learning Framework for Text
DeLFT DeLFT (Deep Learning Framework for Text) is a Keras and TensorFlow framework for text processing, focusing on sequence labelling (e.g. named ent
Open Sound Strip, Sequence or Record in Audacity
Audacity Tools For Blender Sound editing in Blender Video Sequence Editor with Audacity integrated. Send/receive the full edited sequence or single st
A very simple framework for state-of-the-art Natural Language Processing (NLP)
A very simple framework for state-of-the-art NLP. Developed by Humboldt University of Berlin and friends. Flair is: A powerful NLP library. Flair allo
Sequence learning toolkit for Python
seqlearn seqlearn is a sequence classification toolkit for Python. It is designed to extend scikit-learn and offer as similar as possible an API. Comp
Implementation of SETR model, Original paper: Rethinking Semantic Segmentation from a Sequence-to-Sequence Perspective with Transformers.
SETR - Pytorch Since the original paper (Rethinking Semantic Segmentation from a Sequence-to-Sequence Perspective with Transformers.) has no official
Bidirectional LSTM-CRF and ELMo for Named-Entity Recognition, Part-of-Speech Tagging and so on.
anaGo anaGo is a Python library for sequence labeling(NER, PoS Tagging,...), implemented in Keras. anaGo can solve sequence labeling tasks such as nam
Kashgari is a production-level NLP Transfer learning framework built on top of tf.keras for text-labeling and text-classification, includes Word2Vec, BERT, and GPT2 Language Embedding.
Kashgari Overview | Performance | Installation | Documentation | Contributing 🎉 🎉 🎉 We released the 2.0.0 version with TF2 Support. 🎉 🎉 🎉 If you
Sequence-to-sequence framework with a focus on Neural Machine Translation based on Apache MXNet
Sockeye This package contains the Sockeye project, an open-source sequence-to-sequence framework for Neural Machine Translation based on Apache MXNet
DELTA is a deep learning based natural language and speech processing platform.
DELTA - A DEep learning Language Technology plAtform What is DELTA? DELTA is a deep learning based end-to-end natural language and speech processing p
A very simple framework for state-of-the-art Natural Language Processing (NLP)
A very simple framework for state-of-the-art NLP. Developed by Humboldt University of Berlin and friends. IMPORTANT: (30.08.2020) We moved our models
Facebook AI Research Sequence-to-Sequence Toolkit written in Python.
Fairseq(-py) is a sequence modeling toolkit that allows researchers and developers to train custom models for translation, summarization, language mod