woyijkl1's starred repositories
sentence-transformers
Multilingual Sentence & Image Embeddings with BERT
cmake-cookbook
CMake Cookbook recipes.
CTranslate2
Fast inference engine for Transformer models
IOS13-SimulateTouch
iOS Automation Framework iOS Touch Simulation Library
spellcorrect
A program to correct non-word spelling error in sentences using ngram MAP Language Models, Noisy Channel Model, Error Confusion Matrix and Damerau-Levenshtein Edit Distance.
sentencepiece
Unsupervised text tokenizer for Neural Network-based text generation.
tokenizers
💥 Fast State-of-the-Art Tokenizers optimized for Research and Production
subword-nmt
Unsupervised Word Segmentation for Neural Machine Translation and Text Generation
awesome-search
Awesome Search - this is all about the (e-commerce, but not only) search and its awesomeness
StandAloneSpellingCorrection
Repository for Findings of EMNLP 2020 "Context-aware Stand-alone Neural Spelling Correction"
NLPer-Arsenal
收录NLP竞赛策略实现、各任务baseline、相关竞赛经验贴（当前赛事、往期赛事、训练赛）、NLP会议时间、常用自媒体、GPU推荐等，持续更新中
Confusionset-guided-Pointer-Networks-for-Chinese-Spelling-Check
This repository is for the paper "Confusionset-guided Pointer Networks for Chinese Spelling Check"
pytorch-lightning
Pretrain, finetune and deploy AI models on multiple GPUs, TPUs with zero code changes.
tensor2tensor
Library of deep learning models and datasets designed to make deep learning more accessible and accelerate ML research.
TwoWaysToImproveCSC
This is the official code for paper titled "Exploration and Exploitation: Two Ways to Improve Chinese Spelling Correction Models".
BertBasedCorrectionModels
PyTorch impelementations of BERT-based Spelling Error Correction Models. 基于BERT的文本纠错模型，使用PyTorch实现。
Automatic-Corpus-Generation
This repository is for the paper "A Hybrid Approach to Automatic Corpus Generation for Chinese Spelling Check"
CIKM2020_DMT
Deep Multifaceted Transformers for Multi-objective Ranking in Large-Scale E-commerce Recommender Systems, CIKM 2020
Awesome-Deep-Learning-Papers-for-Search-Recommendation-Advertising
Awesome Deep Learning papers for industrial Search, Recommendation and Advertising. They focus on Embedding, Matching, Ranking (CTR and CVR prediction), Post Ranking, Multi-task Learning, Graph Neural Networks, Transfer Learning, Reinforcement Learning, Self-supervised Learning and so on.
rtb-papers
A collection of research and survey papers of real-time bidding (RTB) based display advertising techniques.