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allennlp

An open-source NLP research library, built on PyTorch.

assert

autoencoder-with-pytorch

bdc_2018

Preliminary rank_13

ccf-bdci-sentiment-analysis-baseline

The code for CCF-BDCI-Sentiment-Analysis-Baseline

codebert

CodeBERT

codexglue

CodeXGLUE

comet-commonsense

Code for ACL 2019 Paper: "COMET: Commonsense Transformers for Automatic Knowledge Graph Construction" https://arxiv.org/abs/1906.05317

concode

Mapping Language to Code in a Programmatic Context

cppprimer

:books: Solutions for C++ Primer 5th exercises.

csharp

csharpgl

:green_apple: Object Oriented OpenGL in C#.

csharpscripts

Collection of C# scripts

ctrnet-tool

This's the tool for CTR, including FM, FFM, NFFM and so on.

dialog-to-action

The code for the 2018 NeurIPS paper "Dialog-to-Action: Conversational Question Answering Over a Large-Scale Knowledge Base"

ea-vq-vae-1

This repo provides the code for the ACL 2020 paper "Evidence-Aware Inferential Text Generation with Vector Quantised Variational AutoEncoder"

ember-paper

The Ember approach to Material Design.

emnlp2019-split-and-recombine

The code of EMNLP 2019 paper "A Split-and-Recombine Approach for Follow-up Query Analysis"

esim

ESIM model implemented by tensorflow

icme2019-ctr

The Code for ICME2019 Grand Challenge: Short Video Understanding (Single Model Ranks 6th)

imagenet

Trial on kaggle imagenet object localization by yolo v3 in google cloud

javascript

PubNub JavaScript SDK. https://www.pubnub.com/docs/javascript/pubnub-javascript-sdk-v4

laprador

🦮 Code and pretrained models for Findings of ACL 2022 paper "LaPraDoR: Unsupervised Pretrained Dense Retriever for Zero-Shot Text Retrieval"

learningtoupdatenlcomments

Learning to Update Natural Language Comments Based on Code Changes: Artifact

msmarco-passage-ranking

MS MARCO(Microsoft Machine Reading Comprehension) is a large scale dataset focused on machine reading comprehension, question answering, and passage ranking. A variant of this task will be the part of TREC and AFIRM 2019. For Updates about TREC 2019 please follow This Repository Passage Reranking task Task Given a query q and a the 1000 most relevant passages P = p1, p2, p3,... p1000, as retrieved by BM25 a succeful system is expected to rerank the most relevant passage as high as possible. For this task not all 1000 relevant items have a human labeled relevant passage. Evaluation will be done using MRR

paipaidai2018_rank16

ESIM model with lanuage model

paperplane

MediaPlay DirectShow VS2013 C#

prophetnet

ProphetNet: Predicting Future N-gram for Sequence-to-Sequence Pre-training https://arxiv.org/pdf/2001.04063.pdf

py-faster-rcnn

Faster R-CNN (Python implementation) -- see https://github.com/ShaoqingRen/faster_rcnn for the official MATLAB version

pytorch-vq-vae

PyTorch implementation of VQ-VAE by Aäron van den Oord et al.